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Milvus MCP Server

MCP server from Zilliz for connecting Claude to Milvus vector database collections, text search, vector search, hybrid search, inserts, deletes, indexes, collection loading, database switching, and collection metadata.

by Zilliz·added 2026-06-06·

Claude CodeClaude Desktop

HarnessClaude CodeClaude Desktop

Install

Source

git clone https://github.com/zilliztech/mcp-server-milvus.git && cd mcp-server-milvus && uv run src/mcp_server_milvus/server.py --milvus-uri <milvus-uri>

Readiness

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Safety notesPresent
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Documentation Source repository Registry JSON · LLM text

Review first — review before installing

Open the source and read safety notes before installing.

Safety notes

Milvus MCP can read collection metadata, query collections, and run text, vector, text-similarity, multi-vector, and hybrid searches.
Write-capable tools can create collections, insert data, upsert data, delete entities, create indexes, bulk insert records, load collections, release collections, and switch databases.
The README notes that the environment file has higher priority than command-line arguments, so stale or unexpected environment settings can silently change the target Milvus instance.
SSE and Streamable HTTP modes can expose database operations over HTTP and should be network-restricted.
Remote Milvus or Zilliz Cloud credentials should be scoped to the collections and databases Claude is allowed to access.

Privacy notes

Milvus collections can contain embeddings, sparse vectors, scalar fields, IDs, document chunks, metadata, image or multimodal references, query logs, and retrieval results that reveal sensitive project or user data.
Milvus URI, tokens, database names, collection names, vector payloads, filter expressions, and retrieved records should stay out of prompts, issues, logs, screenshots, and committed files.
Search results can include private source content that may be re-exposed in model transcripts or downstream tickets.
HTTP transports, debug tools, query traces, failed-search artifacts, backups, and benchmark datasets need retention and access-control review.

Prerequisites

Python 3.10 or newer.
uv installed for the README's recommended run path.
Running local or remote Milvus instance.
Milvus URI, token, and database name selected for the target environment.
Review of whether stdio, SSE, or Streamable HTTP mode is appropriate for the MCP client.
Human approval policy for collection creation, inserts, upserts, deletes, index changes, database switching, and collection loading or release operations.

Schema details

Install type: cli
Troubleshooting: No

Source repository stats

Scope: Source repo

Collection metadata

Estimated setup: 20 minutes
Difficulty: advanced

Full copyable content

{
  "mcpServers": {
    "milvus": {
      "command": "uv",
      "args": [
        "--directory",
        "mcp-server-milvus",
        "run",
        "src/mcp_server_milvus/server.py",
        "--milvus-uri",
        "<milvus-uri>"
      ]
    }
  }
}

About this resource

Content

Milvus MCP Server is a Zilliz-maintained Model Context Protocol server for Milvus vector database workflows. It gives Claude and other MCP clients access to Milvus collections, text search, vector search, hybrid search, query filters, collection metadata, index operations, inserts, deletes, database switching, and collection load or release operations.

The README documents stdio, SSE, and Streamable HTTP modes. For local Claude or Cursor use, stdio is the safest starting point because the server process stays attached to the MCP client instead of exposing HTTP endpoints.

Source Review

These sources were reviewed on 2026-06-06. The public Milvus website and docs blocked command-line URL checks, and PyPI metadata for the package name points to a different homepage, so this entry intentionally uses only reachable GitHub source evidence from zilliztech/mcp-server-milvus.

Features

Zilliz-maintained MCP server for Milvus.
Stdio, SSE, and Streamable HTTP modes.
Collection listing and collection information tools.
Text search, vector search, text-similarity search, multi-vector search, and hybrid search.
Filtered query operations.
Collection creation with schema and vector configuration.
Insert, upsert, bulk insert, and delete-entity operations.
Index creation and index information tools.
Collection stats, loading progress, load, and release tools.
Database listing and database switching.
Environment-file and command-line configuration for Milvus URI, token, and database.

Installation

Clone the repository and run the server with uv as documented in the README:

git clone https://github.com/zilliztech/mcp-server-milvus.git
cd mcp-server-milvus
uv run src/mcp_server_milvus/server.py --milvus-uri <milvus-uri>

For an MCP client configuration that launches from a checked-out copy:

{
  "mcpServers": {
    "milvus": {
      "command": "uv",
      "args": [
        "--directory",
        "mcp-server-milvus",
        "run",
        "src/mcp_server_milvus/server.py",
        "--milvus-uri",
        "<milvus-uri>"
      ]
    }
  }
}

Review the target URI, token, database, and environment file before starting the server. The README says the environment file takes priority over command-line arguments.

Use Cases

Ask Claude to list Milvus collections before selecting a retrieval source.
Inspect collection metadata and stats while debugging ingestion.
Run vector, text, or hybrid searches with explicit limits and output fields.
Query collections with filter expressions.
Create an experimental collection for a local evaluation.
Insert or upsert curated records after reviewing the target collection and schema.
Delete entities with a reviewed filter expression.
Load or release collections while troubleshooting serving state.

Safety and Privacy

Milvus MCP is a database control surface. It can retrieve sensitive indexed content and can also mutate collections, indexes, entities, and database selection. Require human approval for writes, deletes, index creation, database switching, load, and release operations.

Treat vectors and metadata as sensitive even when source text is not returned. Embeddings, IDs, filters, collection names, and retrieval results can reveal private context. Restrict SSE and Streamable HTTP modes to trusted networks and avoid leaking Milvus tokens or query results into prompts, logs, or committed configuration.

Duplicate Check

Existing content includes a general Milvus tools entry in content/tools, but no Milvus MCP Server entry was found in content/mcp. This submission is scoped to zilliztech/mcp-server-milvus, the MCP server, and does not change the existing Milvus database listing.

#milvus#vector-database#embeddings#retrieval#zilliz

Source citations

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