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ainative-zerodb-mcp-server

vector-databasesknowledge-and-memoryrag-systems

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ZeroDB MCP Server v2.0.8

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Enterprise-grade Model Context Protocol (MCP) server providing full access to ZeroDB's vector search, quantum compression, NoSQL operations, and persistent memory for AI agents.

Key Features

  • 60 Complete Operations - Full API coverage across all ZeroDB capabilities
  • Vector Search - Semantic similarity search with 1536-dimensional embeddings
  • Quantum Compression - Advanced vector compression using quantum algorithms
  • NoSQL Tables - Flexible table operations for structured data
  • File Storage - Secure file upload, download, and management
  • Event System - Event-driven architecture with pub/sub support
  • Project Management - Multi-tenant project isolation and management
  • RLHF Integration - Reinforcement Learning from Human Feedback collection
  • Admin Tools - System monitoring, optimization, and health checks
  • Enterprise Security - JWT authentication with automatic token renewal
  • 90%+ Test Coverage - Comprehensive test suite for production reliability

Table of Contents


Installation

NPM Global Installation

npm install -g ainative-zerodb-mcp-server

NPX (No Installation Required)

npx ainative-zerodb-mcp-server

Requirements

  • Node.js >= 18.0.0
  • NPM >= 9.0.0
  • ZeroDB account with API credentials (see below)

Getting Started

Step 1: Create Your ZeroDB Account

Before using the MCP server, you need a ZeroDB account and project.

Option A: Register via Web (Recommended)

Visit: https://api.ainative.studio/docs

  1. Click on "Register User" endpoint
  2. Use the "Try it out" feature
  3. Enter your email, password, and username

Option B: Register via API

curl -X POST 'https://api.ainative.studio/v1/public/auth/register' \ -H 'Content-Type: application/json' \ -d '{ "email": "your-email@example.com", "password": "YourSecurePassword123!", "username": "yourname" }'

Response:

{ "email": "your-email@example.com", "id": "user-uuid-here", "username": "yourname" }

Step 2: Create a Project

After registration, create a project to get your PROJECT_ID:

# 1. Login to get your access token curl -X POST 'https://api.ainative.studio/v1/public/auth/login-json' \ -H 'Content-Type: application/json' \ -d '{ "username": "your-email@example.com", "password": "YourSecurePassword123!" }'

Response:

{ "access_token": "eyJhbGc...", "token_type": "bearer", "expires_in": 1800 }
# 2. Create a project using your token curl -X POST 'https://api.ainative.studio/v1/public/projects' \ -H 'Authorization: Bearer YOUR_ACCESS_TOKEN_HERE' \ -H 'Content-Type: application/json' \ -d '{ "name": "My ZeroDB MCP Project", "description": "Project for Claude Desktop MCP integration" }'

Response:

{ "id": "550e8400-e29b-41d4-a716-446655440000", "name": "My ZeroDB MCP Project", "status": "ACTIVE", ... }

Save this Project ID! You'll need it for the MCP configuration.


Quick Start

Step 3: Configure Claude Desktop

Add to your Claude Desktop configuration file:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "zerodb": { "command": "npx", "args": ["ainative-zerodb-mcp-server"], "env": { "ZERODB_API_URL": "https://api.ainative.studio", "ZERODB_PROJECT_ID": "your-project-id-here", "ZERODB_USERNAME": "your-email@example.com", "ZERODB_PASSWORD": "your-password", "MCP_CONTEXT_WINDOW": "8192", "MCP_RETENTION_DAYS": "30" } } } }

Step 4: Restart Claude Desktop

After saving the configuration, restart Claude Desktop to activate the MCP server.

Step 5: Test Your First Operation

In Claude Desktop, try:

Store a memory: "This is my first ZeroDB memory entry"

Claude will use the zerodb_store_memory tool to persist this information.


API Reference

All 60 operations are organized into 9 categories. Each operation is exposed as an MCP tool that Claude can invoke.

Memory Operations

1. zerodb_store_memory

Store agent memory in ZeroDB for persistent context across sessions.

Parameters:

  • content (string, required) - Memory content to store
  • role (string, required) - Message role: "user", "assistant", or "system"
  • session_id (string, optional) - Session identifier (auto-generated if not provided)
  • agent_id (string, optional) - Agent identifier (auto-generated if not provided)
  • metadata (object, optional) - Additional metadata

Returns:

{ "memory_id": "uuid", "created_at": "2025-10-14T12:00:00Z" }

Example:

{ "content": "User prefers dark mode and TypeScript", "role": "system", "metadata": { "category": "preferences" } }

2. zerodb_search_memory

Search agent memory using semantic similarity.

Parameters:

  • query (string, required) - Search query
  • session_id (string, optional) - Filter by session
  • agent_id (string, optional) - Filter by agent
  • role (string, optional) - Filter by role
  • limit (number, optional) - Max results (default: 10)

Returns:

{ "memories": [ { "memory_id": "uuid", "content": "string", "role": "user|assistant|system", "created_at": "timestamp", "similarity_score": 0.95 } ] }

Example:

{ "query": "What were the user's preferences?", "limit": 5 }

3. zerodb_get_context

Get agent context window for current session, optimized for token limits.

Parameters:

  • session_id (string, required) - Session identifier
  • agent_id (string, optional) - Agent identifier
  • max_tokens (number, optional) - Max tokens in context (default: 8192)

Returns:

{ "session_id": "uuid", "agent_id": "uuid", "total_tokens": 1024, "memory_count": 15, "messages": [ { "role": "user", "content": "string", "timestamp": "2025-10-14T12:00:00Z" } ] }

Example:

{ "session_id": "session-123", "max_tokens": 4096 }

Vector Operations

4. zerodb_store_vector

Store vector embedding with metadata (exactly 1536 dimensions).

Parameters:

  • vector_embedding (array[number], required) - 1536-dimensional vector
  • document (string, required) - Source document text
  • metadata (object, optional) - Document metadata
  • namespace (string, optional) - Vector namespace (default: "windsurf")

Returns:

{ "vector_id": "uuid", "namespace": "windsurf" }

Example:

{ "vector_embedding": [0.1, 0.2, ..., 0.9], // 1536 values "document": "This is the source text", "metadata": { "source": "documentation", "page": 42 } }

5. zerodb_batch_upsert_vectors

Batch upsert multiple vectors for improved performance.

Parameters:

  • vectors (array, required) - Array of vector objects
    • vector_embedding (array[number], required) - 1536-dimensional vector
    • document (string, required) - Source document
    • metadata (object, optional) - Document metadata
  • namespace (string, optional) - Vector namespace

Returns:

{ "success_count": 100, "failed_count": 0, "vector_ids": ["uuid1", "uuid2", ...] }

Example:

{ "vectors": [ { "vector_embedding": [...], "document": "Document 1", "metadata": {"index": 1} }, { "vector_embedding": [...], "document": "Document 2", "metadata": {"index": 2} } ], "namespace": "knowledge-base" }

6. zerodb_search_vectors

Search vectors using semantic similarity.

Parameters:

  • query_vector (array[number], required) - 1536-dimensional query vector
  • namespace (string, optional) - Vector namespace
  • limit (number, optional) - Max results (default: 10)
  • threshold (number, optional) - Similarity threshold 0-1 (default: 0.7)

Returns:

{ "vectors": [ { "vector_id": "uuid", "document": "string", "similarity_score": 0.95, "metadata": {} } ] }

Example:

{ "query_vector": [...], // 1536 values "namespace": "windsurf", "limit": 20, "threshold": 0.8 }

7. zerodb_delete_vector

Delete a specific vector by ID.

Parameters:

  • vector_id (string, required) - Vector UUID to delete

Returns:

{ "success": true, "deleted_id": "uuid" }

Example:

{ "vector_id": "123e4567-e89b-12d3-a456-426614174000" }

8. zerodb_get_vector

Retrieve a specific vector by ID.

Parameters:

  • vector_id (string, required) - Vector UUID to retrieve

Returns:

{ "vector_id": "uuid", "vector_embedding": [...], "document": "string", "metadata": {}, "created_at": "timestamp" }

Example:

{ "vector_id": "123e4567-e89b-12d3-a456-426614174000" }

9. zerodb_list_vectors

List vectors with pagination and filtering.

Parameters:

  • namespace (string, optional) - Filter by namespace
  • limit (number, optional) - Results per page (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)

Returns:

{ "vectors": [...], "total_count": 1000, "limit": 50, "offset": 0 }

Example:

{ "namespace": "windsurf", "limit": 100, "offset": 200 }

10. zerodb_vector_stats

Get statistics about vector storage.

Parameters:

  • namespace (string, optional) - Filter by namespace

Returns:

{ "total_vectors": 10000, "namespaces": { "windsurf": 5000, "default": 5000 }, "storage_bytes": 1048576, "avg_dimension": 1536 }

Example:

{ "namespace": "windsurf" }

11. zerodb_create_vector_index

Create a vector search index for improved performance.

Parameters:

  • namespace (string, required) - Namespace to index
  • index_type (string, optional) - Index type: "ivfflat" or "hnsw" (default: "hnsw")
  • params (object, optional) - Index-specific parameters

Returns:

{ "index_id": "uuid", "namespace": "windsurf", "index_type": "hnsw", "status": "created" }

Example:

{ "namespace": "windsurf", "index_type": "hnsw", "params": { "m": 16, "ef_construction": 200 } }

12. zerodb_optimize_vectors

Optimize vector storage and indexes.

Parameters:

  • namespace (string, optional) - Namespace to optimize

Returns:

{ "optimized": true, "space_saved_bytes": 102400, "duration_ms": 1500 }

Example:

{ "namespace": "windsurf" }

13. zerodb_export_vectors

Export vectors to external format.

Parameters:

  • namespace (string, required) - Namespace to export
  • format (string, optional) - Export format: "json" or "csv" (default: "json")
  • include_embeddings (boolean, optional) - Include vector data (default: false)

Returns:

{ "export_id": "uuid", "download_url": "https://...", "expires_at": "timestamp" }

Example:

{ "namespace": "windsurf", "format": "json", "include_embeddings": true }

Quantum Operations

14. zerodb_quantum_compress

Compress vector using quantum algorithms for reduced storage.

Parameters:

  • vector_embedding (array[number], required) - 1536-dimensional vector to compress
  • compression_ratio (number, optional) - Target ratio 0-1 (default: 0.5)
  • algorithm (string, optional) - Algorithm: "qaoa" or "vqe" (default: "qaoa")

Returns:

{ "compressed_vector": [...], "original_dimensions": 1536, "compressed_dimensions": 768, "compression_ratio": 0.5, "fidelity_score": 0.98 }

Example:

{ "vector_embedding": [...], "compression_ratio": 0.6, "algorithm": "qaoa" }

15. zerodb_quantum_decompress

Decompress quantum-compressed vector.

Parameters:

  • compressed_vector (array[number], required) - Compressed vector data
  • original_dimensions (number, required) - Original dimension count

Returns:

{ "decompressed_vector": [...], "dimensions": 1536, "reconstruction_error": 0.02 }

Example:

{ "compressed_vector": [...], "original_dimensions": 1536 }

16. zerodb_quantum_hybrid_search

Perform hybrid search using quantum-enhanced similarity.

Parameters:

  • query_vector (array[number], required) - 1536-dimensional query
  • namespace (string, optional) - Vector namespace
  • limit (number, optional) - Max results (default: 10)
  • quantum_weight (number, optional) - Quantum influence 0-1 (default: 0.5)

Returns:

{ "vectors": [ { "vector_id": "uuid", "document": "string", "similarity_score": 0.96, "quantum_score": 0.94, "hybrid_score": 0.95 } ] }

Example:

{ "query_vector": [...], "namespace": "windsurf", "limit": 10, "quantum_weight": 0.7 }

17. zerodb_quantum_optimize

Optimize vector space using quantum optimization.

Parameters:

  • namespace (string, required) - Namespace to optimize
  • optimization_target (string, optional) - "storage" or "search_speed" (default: "storage")

Returns:

{ "optimized": true, "improvement_percentage": 35.5, "duration_ms": 5000 }

Example:

{ "namespace": "windsurf", "optimization_target": "search_speed" }

18. zerodb_quantum_feature_map

Generate quantum feature map for vector.

Parameters:

  • vector_embedding (array[number], required) - 1536-dimensional vector
  • feature_map_type (string, optional) - "zz" or "pauli" (default: "zz")

Returns:

{ "feature_map": [...], "quantum_circuit_depth": 10, "qubit_count": 12 }

Example:

{ "vector_embedding": [...], "feature_map_type": "pauli" }

19. zerodb_quantum_kernel

Compute quantum kernel similarity between vectors.

Parameters:

  • vector_a (array[number], required) - First 1536-dimensional vector
  • vector_b (array[number], required) - Second 1536-dimensional vector
  • kernel_type (string, optional) - "linear" or "rbf" (default: "rbf")

Returns:

{ "kernel_similarity": 0.92, "quantum_advantage": 0.15, "computation_time_ms": 45 }

Example:

{ "vector_a": [...], "vector_b": [...], "kernel_type": "rbf" }

Table/NoSQL Operations

20. zerodb_create_table

Create a new NoSQL table with schema.

Parameters:

  • table_name (string, required) - Table name
  • schema (object, required) - JSON schema definition
  • description (string, optional) - Table description

Returns:

{ "table_id": "uuid", "table_name": "string", "created_at": "timestamp" }

Example:

{ "table_name": "user_profiles", "schema": { "user_id": "uuid", "name": "string", "email": "string", "created_at": "timestamp" }, "description": "User profile information" }

21. zerodb_list_tables

List all tables in project.

Parameters:

  • limit (number, optional) - Results per page (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)

Returns:

{ "tables": [ { "table_id": "uuid", "table_name": "string", "row_count": 1000, "created_at": "timestamp" } ], "total_count": 10 }

Example:

{ "limit": 100, "offset": 0 }

22. zerodb_get_table

Get table details and schema.

Parameters:

  • table_id (string, required) - Table UUID

Returns:

{ "table_id": "uuid", "table_name": "string", "schema": {}, "row_count": 1000, "created_at": "timestamp" }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000" }

23. zerodb_delete_table

Delete a table and all its data.

Parameters:

  • table_id (string, required) - Table UUID to delete

Returns:

{ "success": true, "deleted_id": "uuid", "rows_deleted": 1000 }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000" }

24. zerodb_insert_rows

Insert rows into table.

Parameters:

  • table_id (string, required) - Table UUID
  • rows (array, required) - Array of row objects

Returns:

{ "inserted_count": 100, "row_ids": ["uuid1", "uuid2", ...] }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000", "rows": [ { "user_id": "user-1", "name": "John Doe", "email": "john@example.com" }, { "user_id": "user-2", "name": "Jane Smith", "email": "jane@example.com" } ] }

25. zerodb_query_rows

Query table rows with filters.

Parameters:

  • table_id (string, required) - Table UUID
  • filters (object, optional) - Query filters
  • limit (number, optional) - Max results (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)

Returns:

{ "rows": [...], "total_count": 1000, "limit": 50, "offset": 0 }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000", "filters": { "email": { "$contains": "@example.com" } }, "limit": 100 }

26. zerodb_update_rows

Update rows in table.

Parameters:

  • table_id (string, required) - Table UUID
  • filters (object, required) - Row selection filters
  • updates (object, required) - Fields to update

Returns:

{ "updated_count": 50, "row_ids": ["uuid1", "uuid2", ...] }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000", "filters": { "user_id": "user-1" }, "updates": { "email": "newemail@example.com" } }

27. zerodb_delete_rows

Delete rows from table.

Parameters:

  • table_id (string, required) - Table UUID
  • filters (object, required) - Row selection filters

Returns:

{ "deleted_count": 25, "row_ids": ["uuid1", "uuid2", ...] }

Example:

{ "table_id": "123e4567-e89b-12d3-a456-426614174000", "filters": { "created_at": { "$lt": "2025-01-01" } } }

File Operations

28. zerodb_upload_file

Upload file to ZeroDB storage.

Parameters:

  • file_name (string, required) - File name
  • file_data (string, required) - Base64-encoded file data
  • content_type (string, optional) - MIME type
  • metadata (object, optional) - File metadata

Returns:

{ "file_id": "uuid", "file_name": "string", "size_bytes": 1024, "upload_url": "string" }

Example:

{ "file_name": "document.pdf", "file_data": "base64encodeddata...", "content_type": "application/pdf", "metadata": { "category": "documentation" } }

29. zerodb_download_file

Download file from ZeroDB storage.

Parameters:

  • file_id (string, required) - File UUID

Returns:

{ "file_id": "uuid", "file_name": "string", "file_data": "base64encodeddata...", "content_type": "string", "size_bytes": 1024 }

Example:

{ "file_id": "123e4567-e89b-12d3-a456-426614174000" }

30. zerodb_list_files

List files with pagination.

Parameters:

  • limit (number, optional) - Results per page (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)
  • content_type (string, optional) - Filter by MIME type

Returns:

{ "files": [ { "file_id": "uuid", "file_name": "string", "size_bytes": 1024, "content_type": "string", "created_at": "timestamp" } ], "total_count": 100 }

Example:

{ "limit": 100, "content_type": "application/pdf" }

31. zerodb_delete_file

Delete file from storage.

Parameters:

  • file_id (string, required) - File UUID to delete

Returns:

{ "success": true, "deleted_id": "uuid" }

Example:

{ "file_id": "123e4567-e89b-12d3-a456-426614174000" }

32. zerodb_get_file_metadata

Get file metadata without downloading.

Parameters:

  • file_id (string, required) - File UUID

Returns:

{ "file_id": "uuid", "file_name": "string", "size_bytes": 1024, "content_type": "string", "metadata": {}, "created_at": "timestamp" }

Example:

{ "file_id": "123e4567-e89b-12d3-a456-426614174000" }

33. zerodb_generate_presigned_url

Generate temporary download URL.

Parameters:

  • file_id (string, required) - File UUID
  • expiry_seconds (number, optional) - URL validity (default: 3600)

Returns:

{ "file_id": "uuid", "presigned_url": "https://...", "expires_at": "timestamp" }

Example:

{ "file_id": "123e4567-e89b-12d3-a456-426614174000", "expiry_seconds": 7200 }

Event Operations

34. zerodb_create_event

Create a new event in the event system.

Parameters:

  • event_type (string, required) - Event type identifier
  • event_data (object, required) - Event payload
  • metadata (object, optional) - Event metadata

Returns:

{ "event_id": "uuid", "event_type": "string", "created_at": "timestamp" }

Example:

{ "event_type": "user.signup", "event_data": { "user_id": "user-123", "email": "user@example.com" }, "metadata": { "source": "web" } }

35. zerodb_list_events

List events with filtering and pagination.

Parameters:

  • event_type (string, optional) - Filter by event type
  • start_date (string, optional) - Filter by start date (ISO 8601)
  • end_date (string, optional) - Filter by end date (ISO 8601)
  • limit (number, optional) - Results per page (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)

Returns:

{ "events": [ { "event_id": "uuid", "event_type": "string", "event_data": {}, "created_at": "timestamp" } ], "total_count": 1000 }

Example:

{ "event_type": "user.signup", "start_date": "2025-10-01T00:00:00Z", "limit": 100 }

36. zerodb_get_event

Get specific event by ID.

Parameters:

  • event_id (string, required) - Event UUID

Returns:

{ "event_id": "uuid", "event_type": "string", "event_data": {}, "metadata": {}, "created_at": "timestamp" }

Example:

{ "event_id": "123e4567-e89b-12d3-a456-426614174000" }

37. zerodb_subscribe_events

Subscribe to event stream (WebSocket).

Parameters:

  • event_types (array[string], required) - Event types to subscribe to
  • filters (object, optional) - Additional filters

Returns:

{ "subscription_id": "uuid", "event_types": ["user.signup", "user.login"], "websocket_url": "wss://..." }

Example:

{ "event_types": ["user.signup", "user.login"], "filters": { "source": "web" } }

38. zerodb_event_stats

Get event statistics and analytics.

Parameters:

  • event_type (string, optional) - Filter by event type
  • start_date (string, optional) - Start date (ISO 8601)
  • end_date (string, optional) - End date (ISO 8601)
  • group_by (string, optional) - Group by: "hour", "day", "week" (default: "day")

Returns:

{ "total_events": 10000, "event_types": { "user.signup": 1000, "user.login": 9000 }, "timeline": [ { "date": "2025-10-14", "count": 500 } ] }

Example:

{ "start_date": "2025-10-01T00:00:00Z", "end_date": "2025-10-14T23:59:59Z", "group_by": "day" }

Project Operations

39. zerodb_create_project

Create a new ZeroDB project.

Parameters:

  • project_name (string, required) - Project name
  • description (string, optional) - Project description
  • settings (object, optional) - Project settings

Returns:

{ "project_id": "uuid", "project_name": "string", "created_at": "timestamp" }

Example:

{ "project_name": "My AI Application", "description": "Vector search for customer support", "settings": { "retention_days": 90 } }

40. zerodb_get_project

Get project details.

Parameters:

  • project_id (string, required) - Project UUID

Returns:

{ "project_id": "uuid", "project_name": "string", "description": "string", "settings": {}, "created_at": "timestamp" }

Example:

{ "project_id": "123e4567-e89b-12d3-a456-426614174000" }

41. zerodb_list_projects

List all accessible projects.

Parameters:

  • limit (number, optional) - Results per page (default: 50)
  • offset (number, optional) - Pagination offset (default: 0)

Returns:

{ "projects": [ { "project_id": "uuid", "project_name": "string", "created_at": "timestamp" } ], "total_count": 10 }

Example:

{ "limit": 100 }

42. zerodb_update_project

Update project settings.

Parameters:

  • project_id (string, required) - Project UUID
  • project_name (string, optional) - New project name
  • description (string, optional) - New description
  • settings (object, optional) - Updated settings

Returns:

{ "project_id": "uuid", "updated_fields": ["project_name", "settings"], "updated_at": "timestamp" }

Example:

{ "project_id": "123e4567-e89b-12d3-a456-426614174000", "settings": { "retention_days": 120 } }

43. zerodb_delete_project

Delete a project and all its data.

Parameters:

  • project_id (string, required) - Project UUID to delete
  • confirm (boolean, required) - Must be true to confirm deletion

Returns:

{ "success": true, "deleted_id": "uuid", "deleted_at": "timestamp" }

Example:

{ "project_id": "123e4567-e89b-12d3-a456-426614174000", "confirm": true }

44. zerodb_get_project_stats

Get project usage statistics.

Parameters:

  • project_id (string, required) - Project UUID
  • start_date (string, optional) - Start date (ISO 8601)
  • end_date (string, optional) - End date (ISO 8601)

Returns:

{ "project_id": "uuid", "vector_count": 10000, "memory_count": 5000, "table_count": 10, "file_count": 100, "storage_bytes": 10485760, "api_calls": 50000 }

Example:

{ "project_id": "123e4567-e89b-12d3-a456-426614174000", "start_date": "2025-10-01T00:00:00Z" }

45. zerodb_enable_database

Enable database features for project.

Parameters:

  • project_id (string, required) - Project UUID
  • features (array[string], required) - Features to enable: ["vectors", "tables", "files", "events"]

Returns:

{ "project_id": "uuid", "enabled_features": ["vectors", "tables"], "enabled_at": "timestamp" }

Example:

{ "project_id": "123e4567-e89b-12d3-a456-426614174000", "features": ["vectors", "tables", "files"] }

RLHF Operations

46. zerodb_rlhf_interaction

Collect user interaction for RLHF training.

Parameters:

  • session_id (string, required) - Session identifier
  • user_input (string, required) - User's input
  • agent_response (string, required) - Agent's response
  • feedback_score (number, optional) - User rating 1-5
  • metadata (object, optional) - Additional context

Returns:

{ "interaction_id": "uuid", "collected_at": "timestamp" }

Example:

{ "session_id": "session-123", "user_input": "How do I reset my password?", "agent_response": "You can reset your password by...", "feedback_score": 5, "metadata": { "model": "claude-3-sonnet", "response_time_ms": 1200 } }

47. zerodb_rlhf_agent_feedback

Collect feedback about agent performance.

Parameters:

  • agent_id (string, required) - Agent identifier
  • session_id (string, required) - Session identifier
  • feedback_type (string, required) - "positive" or "negative"
  • feedback_text (string, optional) - Detailed feedback
  • metrics (object, optional) - Performance metrics

Returns:

{ "feedback_id": "uuid", "collected_at": "timestamp" }

Example:

{ "agent_id": "agent-123", "session_id": "session-123", "feedback_type": "positive", "feedback_text": "Very helpful and accurate responses", "metrics": { "accuracy": 0.95, "helpfulness": 0.9 } }

48. zerodb_rlhf_workflow

Collect feedback about workflow completion.

Parameters:

  • workflow_id (string, required) - Workflow identifier
  • session_id (string, required) - Session identifier
  • completed (boolean, required) - Workflow completion status
  • duration_ms (number, optional) - Workflow duration
  • feedback (object, optional) - Workflow feedback

Returns:

{ "workflow_feedback_id": "uuid", "collected_at": "timestamp" }

Example:

{ "workflow_id": "workflow-123", "session_id": "session-123", "completed": true, "duration_ms": 5000, "feedback": { "ease_of_use": 5, "effectiveness": 4 } }

49. zerodb_rlhf_error

Collect error reports for model improvement.

Parameters:

  • session_id (string, required) - Session identifier
  • error_type (string, required) - Error category
  • error_message (string, required) - Error description
  • context (object, optional) - Error context
  • user_impact (string, optional) - Impact level: "low", "medium", "high"

Returns:

{ "error_report_id": "uuid", "collected_at": "timestamp" }

Example:

{ "session_id": "session-123", "error_type": "hallucination", "error_message": "Agent provided incorrect information about product pricing", "context": { "user_query": "What is the price?", "agent_response": "The price is $50" }, "user_impact": "high" }

50. zerodb_rlhf_status

Get RLHF collection status.

Parameters:

  • session_id (string, optional) - Filter by session
  • start_date (string, optional) - Start date (ISO 8601)
  • end_date (string, optional) - End date (ISO 8601)

Returns:

{ "total_interactions": 1000, "avg_feedback_score": 4.2, "positive_feedback": 850, "negative_feedback": 150, "collection_rate": 0.85 }

Example:

{ "start_date": "2025-10-01T00:00:00Z", "end_date": "2025-10-14T23:59:59Z" }

51. zerodb_rlhf_summary

Get RLHF analytics summary.

Parameters:

  • group_by (string, optional) - Group by: "agent", "workflow", "session" (default: "agent")
  • start_date (string, optional) - Start date (ISO 8601)
  • end_date (string, optional) - End date (ISO 8601)

Returns:

{ "summary": [ { "group_id": "agent-123", "interaction_count": 500, "avg_score": 4.5, "improvement_trend": 0.15 } ] }

Example:

{ "group_by": "agent", "start_date": "2025-10-01T00:00:00Z" }

52. zerodb_rlhf_start

Start RLHF collection for session.

Parameters:

  • session_id (string, required) - Session i

服务配置

[{'mcpServers': {'zerodb': {'args': ['ainative-zerodb-mcp-server'], 'command': 'npx', 'env': {'MCP_CONTEXT_WINDOW': '8192', 'MCP_RETENTION_DAYS': '30', 'ZERODB_API_URL': 'https://api.ainative.studio', 'ZERODB_PASSWORD': 'your-password', 'ZERODB_PROJECT_ID': 'your-project-id-here', 'ZERODB_USERNAME': 'your-email@example.com'}}}}]

来源