The request names "chroma" without context, and the only source that names Chroma directly is a Replicate model (ZavyChromaXL, an SDXL image fine-tune) 111, which is an image model rather than a vector database. If you meant the Chroma open-source vector database, it is not among the candidates here; the vector-search products listed below do similar retrieval work.
A question back: Do you mean the Chroma open-source vector database (for embeddings and retrieval), or the Chroma image model on Replicate? If the vector database, tell me your language and whether you want self-hoste
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Qdrantqdrant.techverified and signed
An open-source vector similarity search engine with an API, offering a search-points action for nearest-vector queries 515.
official:MCP server · mcp-server-qdrantSDK · qdrant-clientskill · qdrant-clients-sdkSDK · @qdrant/js-client-restskill · qdrant-search-quality+45 community tools built for it
for agents: search_points · vector · collection_list
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Pineconepinecone.ioverified and signed
A vector database with an MCP server and SDK, offering a search-vector action to find similar records in a namespace 414.
official:MCP server · @pinecone-database/mcpSDK · @pinecone-database/pineconeskill · pinecone+10 community tools built for it
for agents: pinecone · search_vector · get_vector
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Redisredis.iofound in code, not yet checked
A real-time data platform with vector search, offering actions to create HNSW vector indexes on hashes and run KNN similarity search 313.
official:MCP server · Redis MCP ServerSDK · redisskill · redis-coreSDK · redis+38 community tools built for it
for agents: create_vector_index_hash · set_vector_in_hash · vector_search_hash
Sources
- 1Replicate - Run AI with an APIreplicate.com · read 2026-10-29
- 3Redis - Real-time data for agents & appsredis.io · read 2026-10-29
- 4The trusted AI knowledge company | Pineconepinecone.io · read 2026-10-29
- 5Qdrant - Vector Search Engineqdrant.tech · read 2026-10-29
- 11fofr/zavy-chroma-xl-v7: declares "fofr/zavy-chroma-xl-v7" (the record we read and signed)unfragile.ai · read 2026-10-24
- 13Redis MCP Server: declares "create_vector_index_hash" (the record we read)github.com · read 2026-10-24
- 14pinecone: declares "pinecone" (the record we read and signed)unfragile.ai · read 2026-10-24
- 15Qdrant (Activepieces): declares "search_points" (the record we read and signed)unfragile.ai · read 2026-10-24
For agents: the 10 actions behind this answer
fofr/zavy-chroma-xl-v7 · fofr/zavy-chroma-xl-v7 verified and signed
ZavyChromaXL v7, a high contrast and colorful SDXL fine-tune
list_tables · Supabase (Activepieces) verified and signed
List Tables — Returns a list of all public tables and views in the database
create_vector_index_hash · Redis MCP Server found in code, not yet checked
Create a Redis 8 vector similarity index using HNSW on a Redis hash.
pinecone · pinecone verified and signed
Pinecone vector database integration. Streamline your Pinecone development with powerful tools for managing vector indexes, querying data, and rapid prototyping. Use slash commands like /quickstart to generate AGENTS.md files and initialize Python projects and /query to quickly explore indexes. Acce
search_points · Qdrant (Activepieces) verified and signed
Search Points — Search for points closest to your given vector (= embedding)
vector-database · lance-namespace verified and signed
db · db verified and signed
Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, Oracle Vector SDK, administration, app development, performance, security, migrations, and agent-safe database workflows. Use when the user asks to write, edit, rewrite, review, format, debug, tune, or explain SQL; create or refactor PL/SQL; use
· Supabase Realtime website read, tools not yet checked
Build production-grade applications with a Postgres database, Authentication, instant APIs, Realtime, Functions, Storage and Vector embeddings. Start for free.
database · mysql-connector-python verified and signed
mongodb · mongodb verified and signed
Official Claude plugin for MongoDB (MCP Server + Skills). Connect to databases, explore data, manage collections, optimize queries, generate reliable code, implement best practices, develop advanced features, and more.
Labels are the instruments' verdict and are never changed by ranking. Agents and robots get this same answer as JSON at /api/v1/find?q=…&answer=1 and through the MCP server.