com.rationalbloks/mcp

Tools

• bulk_create_graph_nodes

  Create multiple nodes at once (up to 500 per call). Uses Neo4j UNWIND for high performance. Essential for knowledge graph population — create hundreds of entities from a single book chapter or article. Each node needs: entity_id (unique string) and data (properties dict). Example: entity_type: "concept" nodes: [ {"entity_id": "quantum-mechanics-001", "data": {"name": "Quantum Mechanics", "field": "Physics"}}, {"entity_id": "wave-function-001", "data": {"name": "Wave Function", "field": "Physics"}}, {"entity_id": "superposition-001", "data": {"name": "Superposition", "field": "Physics"}} ]

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• bulk_create_graph_relationships

  Create multiple relationships at once (up to 500 per call). Uses Neo4j UNWIND for high performance. Essential for connecting knowledge — link hundreds of concepts, people, and events in one operation. Each relationship needs: from_id, to_id, and optional data (properties). Example: rel_type: "related_to" relationships: [ {"from_id": "quantum-mechanics-001", "to_id": "wave-function-001", "data": {"strength": "strong"}}, {"from_id": "quantum-mechanics-001", "to_id": "superposition-001", "data": {"strength": "strong"}} ]

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• create_graph_node

  Create a single node in a deployed graph project. REQUIRES: Project must be deployed (use deploy_graph_staging first). The entity_type must match an entity key from the project schema. Use get_graph_data_schema to see available entity types and their fields. Example: entity_type: "person" entity_id: "alan-turing-001" data: {"name": "Alan Turing", "birth_year": 1912, "field": "Computer Science"} The entity_id is your unique identifier — use meaningful IDs for knowledge graphs.

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• create_graph_project

  Create a new Neo4j graph database project from a hierarchical JSON schema. ⚠️ GRAPH SCHEMA FORMAT — READ BEFORE CREATING: Graph schemas define nodes (entities) and relationships, NOT flat database tables. Each field is a dict with "type" and optional "required": true (defaults to false). SCHEMA STRUCTURE: { "nodes": { "EntityName": { "description": "What this entity represents", "flat_labels": ["AdditionalLabel"], "schema": { "field_name": {"type": "string", "required": true}, "other_field": {"type": "integer"} } } }, "relationships": { "RELATIONSHIP_TYPE": { "from": "EntityName", "to": "OtherEntity", "cardinality": "MANY_TO_MANY", "data_schema": { "field_name": {"type": "date"} } } } } FIELD TYPES: string, integer, float, boolean, date, json CARDINALITY OPTIONS: ONE_TO_ONE, ONE_TO_MANY, MANY_TO_ONE, MANY_TO_MANY HIERARCHICAL NODES: Nest entities inside parent entities to create type hierarchies. Child entities inherit parent labels automatically. Example: { "nodes": { "Animal": { "description": "Base animal entity", "flat_labels": ["LivingThing"], "schema": { "name": {"type": "string", "required": true}, "habitat": {"type": "string"} }, "Dog": { "description": "A dog (inherits Animal labels)", "flat_labels": ["Pet"], "schema": { "breed": {"type": "string", "required": true}, "trained": {"type": "boolean"} } } } }, "relationships": { "OWNS": { "from": "Person", "to": "Animal", "cardinality": "ONE_TO_MANY" } } } RULES: 1. "nodes" key is REQUIRED — must contain at least one entity 2. Each entity needs "description" and "schema" with field definitions 3. Each field is {"type": "...", "required": true/false} — required defaults to false 4. Relationship "from"/"to" must reference defined node names 5. Relationship types should be UPPER_SNAKE_CASE 6. Entity names should be PascalCase 7. Automatic fields (id, created_at, updated_at) are NOT needed 8. Use get_graph_template_schemas FIRST to see valid examples WORKFLOW: 1. Use get_graph_template_schemas to see valid examples 2. Create schema following the rules above 3. Call this tool 4. Monitor with get_job_status (2-5 min deployment) After creation, use get_job_status with returned job_id to monitor deployment.

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• create_graph_relationship

  Create a relationship between two nodes in a deployed graph project. The rel_type must match a relationship key from the project schema. Use get_graph_data_schema to see available relationship types. Example: rel_type: "authored" from_id: "alan-turing-001" to_id: "on-computable-numbers-001" data: {"year": 1936} The from_id and to_id must be entity_ids of existing nodes.

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• create_project

  Create a new RationalBloks project from a JSON schema. ⚠️ CRITICAL RULES - READ BEFORE CREATING SCHEMA: 1. FLAT FORMAT (REQUIRED): ✅ CORRECT: {users: {email: {type: "string", max_length: 255}}} ❌ WRONG: {users: {fields: {email: {type: "string"}}}} DO NOT nest under 'fields' key! 2. FIELD TYPE REQUIREMENTS: • string: MUST have "max_length" (e.g., max_length: 255) • decimal: MUST have "precision" and "scale" (e.g., precision: 10, scale: 2) • datetime: Use "datetime" NOT "timestamp" • ALL fields: MUST have "type" property 3. AUTOMATIC FIELDS (DON'T define): • id (uuid, primary key) • created_at (datetime) • updated_at (datetime) 4. USER AUTHENTICATION: ❌ NEVER create "users", "customers", "employees" tables with email/password ✅ USE built-in app_users table Example: { "employee_profiles": { "user_id": {type: "uuid", foreign_key: "app_users.id", required: true}, "department": {type: "string", max_length: 100} } } 5. AUTHORIZATION: Add user_id → app_users.id to enable "only see your own data" Example: { "orders": { "user_id": {type: "uuid", foreign_key: "app_users.id"}, "total": {type: "decimal", precision: 10, scale: 2} } } 6. FIELD OPTIONS: • required: true/false • unique: true/false • default: any value • enum: ["val1", "val2"] • foreign_key: "table.id" AVAILABLE TYPES: string, text, integer, decimal, boolean, uuid, date, datetime, json, uuid_array, integer_array, text_array, float_array Array types store PostgreSQL native arrays with automatic GIN indexing: • uuid_array: UUID[] — for sets of references (e.g., tensor coordinates) • integer_array: BIGINT[] — for dimension indices, integer sets • text_array: TEXT[] — for tags, categories, label sets • float_array: DOUBLE PRECISION[] — for weight vectors, scores GIN-indexed operators: @> (contains), <@ (contained_by), && (overlaps) BACKEND ENGINE: • python (default): FastAPI backend — mature, full-featured • rust: Axum backend — faster cold starts, lower memory, high performance WORKFLOW: 1. Use get_template_schemas FIRST to see valid examples 2. Create schema following ALL rules above 3. Call this tool (optionally choose backend_type: "python" or "rust") 4. Monitor with get_job_status (2-5 min deployment) After creation, use get_job_status with returned job_id to monitor deployment.

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• delete_graph_node

  Delete a node and all its relationships from a deployed graph project. ⚠️ This also removes all relationships connected to this node (DETACH DELETE).

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• delete_graph_project

  Delete a graph project (removes GitHub repo, K8s deployments, Neo4j database, and credentials)

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• delete_graph_relationship

  Delete a specific relationship by its internal ID. Use get_node_relationships to find relationship IDs.

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• delete_module

  Remove a module: its pods stop and it leaves the project and its CORS origins. DESTRUCTIVE. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• delete_project

  Delete a project (removes GitHub repo, K8s deployments, and database)

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• deploy_destructive

  Deploy a plan that drops data, of a relational or a graph project. DESTRUCTIVE: the tables, fields, entities or relationships the plan drops lose their data. environment 'staging' deploys the saved schema, 'production' promotes staging. Use it only after a deploy tool (deploy_staging, deploy_production, deploy_graph_staging, deploy_graph_production) refused the plan, naming its drops, and those drops are intended. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status. One operation runs on a project at a time: while another runs, the call is refused and the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• deploy_graph_production

  Promote graph staging to production. Creates a separate production Neo4j instance with its own credentials and database. Requires paid plan.

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• deploy_graph_staging

  Deploy a graph project to the staging environment. This triggers: (1) Schema validation, (2) Neo4j entity code generation, (3) Docker image build, (4) GitHub commit, (5) Kubernetes deployment with Neo4j instance. The operation is ASYNCHRONOUS — returns immediately with a job_id. Use get_job_status to monitor progress. Deployment typically takes 2-5 minutes. Use get_graph_project_info to verify deployment succeeded.

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• deploy_module

  Deploy a new module from a GitHub repository onto the project's resource pool: a frontblok module is a Vite frontend, a logicblok module a backend built from its Dockerfile that serves port 8000 with GET /health. Its job clones the repository (the default branch head, or git_ref), builds it and serves it at the module_url the answer names; the project's CORS origins take the module in. A private repository needs the RationalBloks GitHub App installed on it. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• deploy_production

  Promote staging to production (requires paid plan)

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• deploy_staging

  Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.

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• drop_schema_items

  Drop tables or fields from a project's saved schema (saves to database, does NOT deploy). DESTRUCTIVE: the next deploy drops their data. OPERATIONS (applied in order and all together): • {"op": "drop_table", "table": "clocks"} • {"op": "drop_field", "table": "parameters", "field": "is_clock"} A drop that cannot be applied (a table or field that is not there, a schema the deploy would refuse, such as a field another reads) refuses them all, naming it, and nothing is saved. The answer carries 'applied', 'diff', 'plan' and the new 'version'. WORKFLOW: 1. preview_schema_change with the same operations: check 'diff' and 'plan' 2. drop_schema_items (pass expected_version to be refused if someone else saved meanwhile) 3. deploy_staging refuses the plan and names its drops; deploy_destructive applies it, then get_job_status

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• freeze_module

  Stop a module's pods (scale to 0), remembering how many it ran; unfreeze_module starts them again. Freezing a frozen module changes nothing. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• fulltext_search_graph

  Search across ALL string properties of ALL nodes in a deployed graph using free-text queries. Unlike search_graph_nodes (which filters by specific property), this searches every text field at once. Perfect for finding knowledge when you don't know which property contains the answer. Example: query "quantum" searches name, description, summary, notes, and all other string fields. Returns nodes with _match_fields showing which properties matched. Optionally filter by entity_type to narrow results.

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• get_graph_data_schema

  Get the runtime schema of a DEPLOYED graph project — shows the actual entity types and relationship types available for data operations. Returns: Available entity keys (for create_graph_node, list_graph_nodes, etc.) and relationship keys (for create_graph_relationship, etc.). ⭐ USE THIS FIRST before creating nodes/relationships to know what entity_type and rel_type values are valid.

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• get_graph_node

  Get a specific node by its entity_id from a deployed graph project. Returns all node properties including created_at and updated_at timestamps.

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• get_graph_project_info

  Get detailed graph project information including Kubernetes deployment status, Neo4j database health, pod status, and resource usage. Use this after deployment to verify the graph project is running correctly.

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• get_graph_schema

  Get the graph schema definition of a project. Returns the hierarchical schema with nodes (entities) and relationships. Graph schemas define entity hierarchies and typed relationships — a different format than relational flat-table schemas.

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• get_graph_schema_at_version

  Get the graph schema as it existed at a specific version/commit. Use get_graph_version_history to find commit SHAs. Useful for comparing schemas across versions or auditing changes.

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• get_graph_statistics

  Get statistics about a deployed graph: total node count, total relationship count, counts per entity type, counts per relationship type. Essential for understanding the current state of a knowledge graph before adding more data.

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• get_graph_template_schemas

  Get pre-built graph template schemas for common use cases. ⭐ USE THIS FIRST when creating a new graph project! Templates show the CORRECT graph schema format with: proper node definitions (description, flat_labels, schema with flat field definitions), relationship configurations (from, to, cardinality, data_schema), and hierarchical entity nesting. Available templates: Social Network (users, posts, follows), Knowledge Graph (topics, articles, authors), Product Catalog (products, categories, suppliers). You can use these templates directly with create_graph_project or modify them for your needs. TIP: Study these templates to understand the correct graph schema format before creating custom schemas.

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• get_graph_version_history

  Get the deployment and version history for a graph project. Shows all schema changes with commit SHAs, timestamps, version numbers, and messages. Use this to find a specific version for rollback operations.

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• get_job_status

  Check the status of a deployment job. STATUS VALUES: pending (job queued), running (deployment in progress), completed (success), failed (deployment failed). TIMELINE: Typical deployment takes 2-5 minutes. If status is 'running' for >10 minutes, check get_project_info for detailed pod status. If status is 'failed', use get_project_info to see deployment errors and check schema format (must be FLAT, no 'fields' nesting).

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• get_node_relationships

  Get all relationships connected to a specific node. Supports direction filtering (incoming, outgoing, both) and relationship type filtering.

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• get_project

  Get detailed information about a specific project

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• get_project_info

  Get detailed project info including deployment status and resource usage. DEPLOYMENT STATUS: Running (healthy), Pending (starting), CrashLoopBackOff (init container failed - usually schema format error), ImagePullBackOff (image build failed). TROUBLESHOOTING: If status is CrashLoopBackOff, the schema is likely in wrong format (nested 'fields' key or missing 'type' properties). Use get_schema to review current schema. If replicas show 0/2, the init container (migration runner) is failing. This is almost always a schema format issue.

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• get_project_storage_usage

  Get object-storage usage for a project: file count and bytes used against the plan limits.

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• get_project_usage

  Get resource usage metrics (CPU, memory) for a project

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• get_schema

  Get the JSON schema definition of a project in FLAT format. Returns the schema structure where each table name maps directly to field definitions. This is the same format required for create_project and update_schema. USE CASES: Review current schema before making updates, copy schema as template for new projects, verify schema structure after deployment, learn the correct schema format by example. The returned schema will be in FLAT format: {table_name: {field_name: {type, properties}}}

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• get_schema_at_version

  Get the schema as it was at a specific version/commit

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• get_schema_reference

  Get the reference for ADVANCED schema features the templates do not show — read this before adding authorization or derived fields to a schema. Covers: __policy__ (relationship-based read/write authorization with single- and multi-hop membership paths, and the rules that decide whether adopting it is safe — it replaces creator-ownership per table and fails closed on a null link), computed columns (read-only values derived from other columns), __constraints__ (composite uniqueness), __audit__ (append-only audit log), and how user foreign keys are attributed on create.

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• get_subscription_status

  Get your subscription tier, limits, and usage

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• get_template_schemas

  Get pre-built template schemas for common use cases. ⭐ USE THIS FIRST when creating a new project! Templates show the CORRECT schema format with: proper FLAT structure (no 'fields' nesting), every field has a 'type' property, foreign key relationships configured correctly, best practices for field naming and types. Available templates: E-commerce (products, orders, customers), Team collaboration (projects, tasks, users), General purpose templates. You can use these templates directly with create_project or modify them for your needs. TIP: Study these templates to understand the correct schema format before creating custom schemas.

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• get_user_info

  Get information about the authenticated user

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• get_version_history

  Get the deployment and version history (git commits) for a project. Shows all schema changes with commit SHA, timestamp, and message. USE CASES: Review what changed between deployments, find the last working version before issues started, get commit SHA for rollback_project.

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• list_clusters

  List your registered BYOC resource pools (client-owned Kubernetes clusters). Each returned cluster has an 'id' you MUST pass as create_project's cluster_id to deploy a project onto your own infrastructure — owned hosting is retired, so every project we operate runs on your own cluster. Registering a pool is a UI action (create a bare Ubuntu box, authorise the key we generate, then we provision it into a cluster automatically) — this tool only lists pools you already registered, it never handles cluster credentials.

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• list_graph_nodes

  List nodes of a specific entity type from a deployed graph project. Supports pagination with limit/offset. Returns nodes ordered by creation date (newest first).

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• list_modules

  List a project's modules and what each runs: module_id (what every module tool takes), name, type (frontblok or logicblok), repository, url, staging_status (not_deployed, deploying, deployed, failed), deployed_at, image (the image of its last successful build, named by the commit it built: <name>:<short sha>-<build time>), replicas (live pods: 0 when frozen, null while the pool is not reporting), CPU and memory, and env_var_names (the names of its environment variables, never their values).

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• list_project_files

  List a project's uploaded files (metadata + public URLs), most recent first. Inspection only — files are not streamed through MCP.

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• list_project_jobs

  List a project's jobs, newest first: every create, deploy, promotion, rollback, resource change and module operation, each with its status, error, failure_side and when it started and ended. A job's record is kept for the life of the project, so this is how to find out what an operation did when you no longer have its job_id (after an interruption, or in a later session): the first job of the job_type you want is the latest. Read older jobs a page at a time with offset; a page shorter than limit is the last.

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• list_projects

  List all your RationalBloks projects with their status and URLs

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• patch_schema

  Change PART of a project's schema (saves to database, does NOT deploy). Send only the change. The server applies it to the saved schema, in order and all together, and keeps every table and field it does not touch — including their identity, so a rename stays a rename and the column keeps its data. OPERATIONS (each one small object, applied in the order given): • {"op": "add_table", "table": "clocks", "definition": {...}} new table, same FLAT rules as create_project • {"op": "drop_table", "table": "clocks"} • {"op": "rename_table", "table": "clocks", "to": "timers"} • {"op": "add_field", "table": "assets", "field": "serial", "definition": {"type": "string", "max_length": 64}} • {"op": "drop_field", "table": "parameters", "field": "is_clock"} • {"op": "rename_field", "table": "parameters", "field": "is_clock", "to": "clock_kind"} • {"op": "set_field", "table": "assets", "field": "name", "properties": {"max_length": 300}} merges; a property set to null is removed • {"op": "set_table", "table": "assets", "properties": {"__audit__": true}} __policy__, __constraints__, __audit__, __admin_write__ ALL OR NOTHING: an operation that cannot be applied — a table or field that is not there, a name already taken, a schema the deploy would refuse — refuses the whole patch, naming the operation, and nothing is saved. EVERY ANSWER IS A DIFF: 'applied' (what each operation did), 'diff' (every changed property by path), 'summary' and 'plan' (the migration a deploy would then run), and 'version' (the schema's version after the change). You never need to read the whole schema back to see what you did. WORKFLOW: 1. get_schema with tables/fields to read the part you are changing (its 'version' is the whole schema's) 2. patch_schema with dry_run=true: check 'diff' and 'plan' 3. patch_schema with the same operations (pass expected_version to be refused if someone else saved meanwhile) 4. deploy_staging (confirm_destructive=true when the plan drops data), then get_job_status

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• preview_schema_change

  Preview a schema change, saving nothing: the one way to see what a change would do before it is saved. Pass ONE of: • operations: the operations patch_schema or drop_schema_items would apply (relational projects) • schema: a whole schema in place of the saved one (relational or graph projects) ANSWER: 'applied' (for operations), 'diff' (every property saving it would change, by path), 'summary' and 'plan' (the migration the next deploy would then run, every table, field, entity or relationship it drops named), and 'version' (the saved schema's: pass it as expected_version to the save that follows, so it is refused if someone saved meanwhile). A relational schema the deploy would refuse is refused here, with the reason.

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• redeploy_module

  Rebuild a module from its repository's default branch head and roll it out, keeping its pod count. Its data and settings are untouched; the project's API (staging and production) and its backend modules restart to take the module's CORS origin. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status, whose result names the image built (its commit); list_modules shows it once done. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• redeploy_project

  Rebuild and roll out a project's staging environment from the schema it runs, with NO schema change, for a relational or a graph project: the current platform release, the project's settings (email, admin users) and its environment take effect. Refused (409) when the saved schema holds changes the last deploy did not apply (deploy_staging deploys those) or when nothing was deployed yet; a save that lands meanwhile is refused rather than deployed. deploy_production rebuilds production the same way when staging runs what production runs. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status. One operation runs on a project at a time: while another runs, the call is refused and the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• rename_project

  Rename a project (changes display name, not project_code)

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• rollback_graph_project

  Rollback a graph project to a previous version. ⚠️ WARNING: This reverts schema AND code to the specified commit. Neo4j data is NOT rolled back. Use get_graph_version_history to find the commit SHA of the version you want to rollback to. After rollback, the graph API will be redeployed with the old schema.

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• rollback_project

  Rollback a project to a previous version. ⚠️ WARNING: This reverts schema AND code to the specified commit. Database data is NOT rolled back. Use get_version_history to find the commit SHA of the version you want to rollback to. After rollback, use get_job_status to monitor the redeployment. Rollback is useful when a schema change breaks deployment.

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• scale_module

  Run 1 or 2 pods of a module (freeze_module stops it). One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• search_graph_nodes

  Search for nodes by property values in a deployed graph project. Supports exact match and contains search (prefix value with ~ for contains). Examples: Exact: filters: {"name": "Alan Turing"} Contains: filters: {"name": "~turing"} (case-insensitive) Combined: entity_type: "person", filters: {"field": "~physics"} Without entity_type, searches ALL node types.

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• set_module_env

  Set a module's environment variables: {NAME: value} sets one, {NAME: null} removes one, and every variable not named is kept. A backend module restarts to take them; a frontend module rebuilds (they are build arguments). Values are stored encrypted and never returned: the answer and list_modules name the variables only. DESTRUCTIVE: a value replaced or removed cannot be read back. CORS_ORIGINS, DEPLOY_* and GITHUB_TOKEN are the platform's. The operation is a job: poll the returned job_id with get_job_status. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• set_module_resources

  Set a module's CPU and memory and rebuild it so its pods take them. The allocation is checked against the resource pool's capacity first; a refused one is restored. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• traverse_graph

  Walk the graph from a starting node, discovering connected knowledge. Returns all nodes reachable within max_depth hops, with their distance from the start. Essential for exploring knowledge graphs — find related concepts, trace connections, discover clusters. Example: Start from "Alan Turing", traverse outgoing relationships up to 3 hops deep: start_entity_type: "person" start_entity_id: "alan-turing-001" max_depth: 3 direction: "outgoing" Supports filtering by relationship types and direction.

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• unfreeze_module

  Start a frozen module's pods again, as many as it ran before the freeze. A running module is left as it is. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• update_graph_node

  Update properties of an existing node in a deployed graph project. Only send the fields you want to change — unspecified fields remain unchanged.

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• update_graph_schema

  Update a graph project's schema (saves to database, does NOT deploy). ⚠️ Follow ALL rules from create_graph_project: • Must have "nodes" key with at least one entity • Each entity needs "description" and "schema" with field definitions • Each field is {"type": "...", "required": true/false} — required defaults to false • Relationships need "from", "to", and "cardinality" • Field types: string, integer, float, boolean, date, json • Relationship types should be UPPER_SNAKE_CASE • Entity names should be PascalCase WORKFLOW: 1. Use get_graph_schema to see current schema 2. Modify following all rules 3. Call update_graph_schema (saves only) 4. Call deploy_graph_staging to apply changes 5. Monitor with get_job_status NOTE: This only saves the schema. You MUST call deploy_graph_staging afterwards to deploy.

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• update_module

  Rename a module, or point it at another GitHub repository, which its next redeploy builds. Pass module_name, github_repo_url or both. One operation runs on a module at a time, and none beside an operation on its project: the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

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• update_schema

  Update a project's schema (saves to database, does NOT deploy). ⚠️ CRITICAL: Follow ALL rules from create_project: • FLAT format (no 'fields' nesting) • string: MUST have max_length • decimal: MUST have precision + scale • Use "datetime" NOT "timestamp" • DON'T define: id, created_at, updated_at • NEVER create users/customers/employees tables (use app_users) ⚠️ MIGRATION RULES: • New fields MUST be "required": false OR have "default" value • Cannot add required field without default to existing tables • Safe: {new_field: {type: "string", max_length: 100, required: false}} WORKFLOW: 1. Use get_schema to see current schema 2. Modify following ALL rules 3. Call update_schema (saves only) 4. Call deploy_staging to apply changes 5. Monitor with get_job_status NOTE: This only saves the schema. You MUST call deploy_staging afterwards to apply changes.

  shallow

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