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MCP Entry

Weaviate MCP Server

Weaviate documents a built-in Model Context Protocol server in the main `weaviate/weaviate` binary from v1.37.1 onward at docs.weaviate.io/weaviate/mcp/mcp-server, exposed as a Streamable HTTP endpoint at `/v1/mcp` on the same port as the REST API (default 8080). Enable with `MCP_SERVER_ENABLED=true`; optional `MCP_SERVER_WRITE_ACCESS_ENABLED=true` registers `weaviate-objects-upsert`. Tools include `weaviate-collections-get-config`, `weaviate-tenants-list`, `weaviate-query-hybrid`, and `weaviate-objects-upsert` (write-gated). Authentication uses existing API keys/Bearer tokens with RBAC permissions `read_mcp`, `create_mcp`, and `update_mcp` per Weaviate 1.37 release notes. The standalone weaviate/mcp-server-weaviate repository is deprecated in favor of this built-in server.

Category Database
Install MCP_SERVER_ENABLED=true on Weaviate v1.37.1+
Runtime Built into Weaviate
weaviatevector-databasehybrid-search

Use cases

  • Let Cursor agents inspect collection schemas before writing hybrid queries
  • Run vector + BM25 hybrid search from MCP without custom glue code
  • List tenants in multi-tenant Weaviate collections for scoped agent retrieval
  • Gate write access separately until `MCP_SERVER_WRITE_ACCESS_ENABLED` is deliberately enabled
  • Replace deprecated standalone mcp-server-weaviate with built-in `/v1/mcp`

Key features

  • Cursor
  • Claude Desktop
  • Claude Code
  • VS Code
  • Codex

Frequently Asked Questions

Is the standalone weaviate/mcp-server-weaviate repo still required?
No—Weaviate docs mark it deprecated; use the built-in server from v1.37.1+.
Are write tools enabled by default?
No—`weaviate-objects-upsert` registers only when `MCP_SERVER_WRITE_ACCESS_ENABLED=true`.
Is this feature stable?
Weaviate 1.37 blog and docs describe MCP as a preview feature that may evolve.

Related

Related

3 Indexed items

Chroma MCP Server

Database

Chroma documents an official Model Context Protocol server in the chroma-core/chroma-mcp repository and docs.trychroma.com/integrations/frameworks/anthropic-mcp, started with `uvx chroma-mcp` over stdio. Tools include `chroma_list_collections`, `chroma_create_collection`, `chroma_peek_collection`, `chroma_modify_collection`, `chroma_delete_collection`, `chroma_add_documents`, `chroma_query_documents`, `chroma_get_documents`, `chroma_update_documents`, and `chroma_delete_documents` per the README. Client types documented: ephemeral (default), persistent (`--client-type persistent --data-dir`), HTTP self-hosted, and Chroma Cloud (`--client-type cloud` with API keys). Embedding function options include default, Cohere, OpenAI, Jina, VoyageAI, and Roboflow per Chroma MCP docs.

LanceDB MCP Server

Database

LanceDB maintains a reference Model Context Protocol server in the lancedb/lancedb-mcp-server repository (linked from lancedb/lancedb issue #2341), implemented with FastMCP and LanceDB embeddings. Tools include `ingest_docs` (embed and store documents), `query_table` (semantic retrieval with configurable top_k and query_type), and `table_details` (schema and row counts) per the README. Configuration uses `uv run lancedb_mcp.py` with environment variables `LANCEDB_URI` (default `~/lancedb`), `TABLE_NAME`, `EMBEDDING_FUNCTION` (default sentence-transformers), and `MODEL_NAME` (default all-MiniLM-L6-v2). The repo describes itself as a basic serverless MCP reference for building more complex LanceDB agent apps—not a full production managed endpoint.

Milvus MCP Server

Database

The zilliztech/mcp-server-milvus project (documented at milvus.io/docs/milvus_and_mcp.md) exposes Milvus vector-database operations to MCP clients such as Claude Desktop and Cursor. The recommended launch path is `uv run src/mcp_server_milvus/server.py --milvus-uri http://localhost:19530` without a separate install step, with optional `MILVUS_URI`, `MILVUS_TOKEN`, and `MILVUS_DB` environment variables. Tools listed in Milvus docs include `milvus-text-search`, `milvus-hybrid-search`, `milvus-multi-vector-search`, `milvus-query`, and `milvus-count` for collection management, semantic retrieval, filtered hybrid search, and entity counts.