observe-community-mcp
Verified Safeby rustomax
Overview
Provides LLMs with intelligent access to Observe platform data through semantic search, automated dataset discovery, and metrics intelligence.
Installation
docker-compose up -dEnvironment Variables
- OBSERVE_CUSTOMER_ID
- OBSERVE_TOKEN
- PUBLIC_KEY_PEM
- SEMANTIC_GRAPH_PASSWORD
- OBSERVE_OTEL_TOKEN
- OBSERVE_OTEL_CUSTOMER_ID
- OBSERVE_OTEL_DOMAIN
- GEMINI_API_KEY
Security Notes
Secrets are managed via environment variables (good practice). JWT authentication with scope-based access control is implemented. Input OPAL queries undergo structural validation and auto-correction. The OpenTelemetry exporter is set to 'insecure=True' by default, which is suitable for local development but should be reviewed for production deployments. Custom OPAL query validation (src/observe/opal_validation.py) helps reduce the risk of malformed queries but relies on the upstream Observe platform for full semantic security validation. Database interactions (src/observe/skills_search.py) use parameterized queries via stored procedures.
Similar Servers
fastmcp
FastMCP is an ergonomic interface for the Model Context Protocol (MCP), providing a comprehensive framework for building and interacting with AI agents, tools, resources, and prompts across various transports and authentication methods.
1xn-vmcp
An open-source platform for composing, customizing, and extending multiple Model Context Protocol (MCP) servers into a single logical, virtual MCP server, enabling fine-grained context engineering for AI workflows and agents.
zeromcp
A minimal, pure Python Model Context Protocol (MCP) server for exposing tools, resources, and prompts via HTTP/SSE and Stdio transports.
mcp-servers
Provides an MCP server for Qdrant vector database integration, enabling AI agents to perform semantic search, store documents, and manage collections with advanced multi-tenant filtering capabilities.