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DimensionPinecone MCP ServerConnect your Pinecone projects to Cursor, Claude, and other AI assistantsMCP Toolbox for DatabasesGoogle's official database MCP toolbox — define AI-accessible database tools via config
FMRS46 / 100 · D74 / 100 · B
Reliability5 / 2013 / 20
Security and permissions8 / 2013 / 20
Maintenance9 / 2017 / 20
Documentation12 / 2016 / 20
Setup experience12 / 2015 / 20
Best for
  • Developers who use Pinecone as part of their technology stack.
  • Users who want to manage Pinecone projects and indexes from within AI coding assistants.
  • Those needing to interact with Pinecone documentation or generate code based on configuration.
  • Teams that want precise control over which database operations an AI can perform, rather than open arbitrary SQL execution
  • Scenarios needing a unified MCP setup across multiple database engines
Not for
  • Users working with indexes without integrated inference, or requiring standalone embeddings, vector search, or assistant features.
  • Scenarios where you need to provide AI assistants with context from your knowledge base (use Pinecone's Assistant MCP for that).
  • Non-developer use cases or non-coding assistant environments.
  • Lightweight cases that just want to run a few ad-hoc SQL queries without maintaining a tools.yaml config (a simpler single-database MCP may be a better fit)
Required permissions
  • Requires a PINECONE_API_KEY environment variable to access your Pinecone project.
  • Allows AI tools to create, list, describe, and delete indexes (actions depend on tool set).
  • Allows upserting and searching records, as well as cross-index search and reranking operations.
  • Allows searching official Pinecone documentation (no API key needed).
  • Database credentials (username/password/connection string) are supplied via env vars or config
  • A tool's actual permission is whatever SQL statement is defined in tools.yaml — designed for least privilege, but misconfiguration can still over-expose access
Risks and side effects
  • API key exposure: ensure the key is kept secure and not committed to version control.
  • Misoperations: AI assistants may accidentally create, modify, or delete indexes; authorize carefully.
  • Cost implications: index operations and data usage may incur charges; monitor usage.
  • Network dependency: requires access to api.pinecone.io; may fail behind firewalls.
  • If tools.yaml defines SQL statements that allow unconstrained writes or deletes, the AI could accidentally modify data
  • The prebuilt toolsets (--prebuilt) favor convenience and may expose broader query capability than a specific business actually needs — use a custom tools.yaml in production
Supported clientsCursor, Claude Desktop, Gemini CLIClaude Code, Gemini CLI, Zed, Antigravity
Tools90