chroma-mcp
Chroma MCP Server - Vector Database Integration for LLM Applications
Decision gist · record as of 2026-08-14
Yes, if you are building LLM applications with Claude Desktop or another MCP-compatible client and need vector search and semantic memory. The low install friction and permissive license make it accessible. However, the aging maintenance status (last release over a year ago) and lack of recent updates warrant caution for production use—verify that the package's stability and feature set meet your needs before committing to it for critical workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Intended for use as an MCP server within Claude Desktop or compatible LLM applications, not as a standalone library.
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production and proprietary projects.
last release 2025-08-14 (365 days) · last repo commit 2025-09-17 · 585 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 168,060 downloads/mo, #10,455 on PyPI
Alternatives
Verify before relying
pip install chroma-mcp
# Configure in Claude Desktop's claude_desktop_config.json:
"chroma": {
"command": "uvx",
"args": ["chroma-mcp"]
}- Whether embedding function persistence works correctly with collections created before Chroma v1.0.0
- Performance characteristics and scalability limits for large document collections
- Stability and breaking-change history across the aging release cycle
What it is and what it does
Chroma MCP Server exposes Chroma's vector database capabilities through the Model Context Protocol, a standardized interface for connecting LLM applications to external tools and data sources. It allows Claude and other MCP-compatible AI models to create and manage document collections, perform semantic and full-text search, and apply metadata filtering—all without the model needing direct database access.
The server supports multiple client modes: ephemeral (in-memory, for testing), persistent (file-based), HTTP (connecting to self-hosted Chroma instances), and cloud (connecting to Chroma Cloud). It integrates with several embedding providers including Cohere, OpenAI, and Voyage AI, and persists the chosen embedding function with each collection so that future queries use the same embeddings automatically.
Use it for
- Add persistent memory to Claude Desktop by storing conversation context or knowledge bases in a vector database for semantic retrieval.
- Build AI-powered search over custom document collections, enabling models to find relevant context using semantic similarity rather than keyword matching.
- Integrate Chroma's vector search into LLM workflows via MCP, allowing models to query and update embeddings as part of their reasoning process.
- Test vector database functionality in development using ephemeral (in-memory) collections without external infrastructure.
- Connect Claude to a self-hosted or cloud-based Chroma instance for production workloads requiring scalability or data isolation.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building LLM applications with Claude Desktop or another MCP-compatible client and need vector search and semantic memory.
The low install friction and permissive license make it accessible. However, the aging maintenance status (last release over a year ago) and lack of recent updates warrant caution for production use—verify that the package's stability and feature set meet your needs before committing to it for critical workflows.
Install
chroma-mcp on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Maintenance status is aging—last release was over a year ago (2025-08-14), though the repository remains active with recent commits (2025-09-17) and modest community engagement (585 stars).
Requires Python 3.10 or later. Intended for use as an MCP server within Claude Desktop or compatible LLM applications, not as a standalone library.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production and proprietary projects.
Quickstart
pip install chroma-mcp
# Configure in Claude Desktop's claude_desktop_config.json:
"chroma": {
"command": "uvx",
"args": ["chroma-mcp"]
}Verify before relying
- Whether embedding function persistence works correctly with collections created before Chroma v1.0.0
- Performance characteristics and scalability limits for large document collections
- Stability and breaking-change history across the aging release cycle
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packageschromadbcoherehttpxmcpopenaipillowpython-dotenvtyping-extensionsvoyageai |
| Maintenance | Aging 365 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 168,060 / month, #10,455 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Topic :: Software Development :: Libraries :: Python Modules |
Evidence: chroma_mcp-0.2.6-py3-none-any.whl
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See also chromadb · chromadb-client · llama-index-vector-stores-chroma · mcp-server-qdrant · tilt-mcp · langchain-chroma · nextcloud-mcp-server · wikipedia-mcp · mcp-types · mcp-server-git