Do both servers run locally?

Both MCP servers run locally over stdio — Pinecone's via npx (@pinecone-database/mcp) and Chroma's via uvx (chroma-mcp) — but they connect to different backends. Pinecone always talks to its managed cloud with a PINECONE_API_KEY, while Chroma connects to a backend you choose: in-memory, on-disk, a self-hosted http server, or Chroma Cloud.

Which handles embeddings for me?

Pinecone does, through integrated inference: create-index-for-model embeds text automatically on upsert and search. With Chroma you supply embeddings or configure external embedding-provider keys, so the embedding step is something you wire up rather than a built-in default.

Can either be self-hosted for free?

Chroma can — it is open source and runs free in ephemeral, persistent, or http (self-hosted server) mode; only Chroma Cloud is paid. Pinecone is a managed cloud service with a free starter tier and paid plans, not something you self-host.

Pinecone vs Chroma

Pinecone MCP and Chroma MCP both give an agent direct access to a vector database for retrieval-augmented workflows, but they reflect two different deployment philosophies. Pinecone's developer server runs over stdio via npx (@pinecone-database/mcp) against your Pinecone account: the agent lists and describes indexes, creates indexes backed by an integrated embedding model, upserts and searches records using that integrated inference (you pass text, Pinecone handles the embeddings), runs a cascading multi-index search, and reranks results. Pinecone is a fully managed, cloud-native serverless service. Chroma's server runs over stdio via uvx (chroma-mcp) and exposes the full collection-and-document surface — create, query, update, and delete documents with semantic, metadata, and full-text search — against a backend you choose: ephemeral in-memory, persistent on disk, an http self-hosted server, or managed Chroma Cloud. Here is a fair look at how they differ on hosting, embeddings, scale, and the work each suits.

How they compare

Dimension	Pinecone	Chroma
Hosting model	Managed, cloud-native, serverless: the database lives in Pinecone's cloud, billed per usage, with no infrastructure to run yourself.	Open source and self-hostable: run in-memory, persistent on disk, or as your own http server — only managed Chroma Cloud is a paid service.
Embeddings	Integrated inference is a first-class path: create-index-for-model embeds text for you on upsert and search, so no separate embedding step is needed.	Bring your own embeddings or set per-provider keys to call external embedding APIs; embedding is configured rather than built into the core flow.
Tool surface	Index- and record-centric: list/describe indexes and stats, create-index-for-model, upsert/search records, cascading-search, and rerank-documents, plus docs search.	Full database surface: list/create/inspect/modify/delete collections, and add/query/get/update/delete documents with semantic, metadata, and full-text search.
Scale and cost	Built to scale automatically to large production workloads with managed reliability; you pay for storage, queries, embedding, and reranking.	Excellent for prototypes and self-hosted use at no cost; single-node deployments are strongest at smaller scales, with Chroma Cloud for managed scaling.
Best-fit task	A production RAG backend where you want managed scaling and integrated embeddings without operating any infrastructure.	A laptop prototype, research project, or self-hosted store where you want zero cost, full control of the backend, and the same tools from dev to cloud.

Verdict

Pick by how much infrastructure you want to own. Reach for Pinecone MCP when you want a fully managed, serverless vector database that scales automatically for production RAG, and you value integrated inference — passing text and letting Pinecone handle the embeddings — plus built-in reranking and cascading multi-index search. Reach for Chroma MCP when you want to start free on a laptop or self-host: its ephemeral, persistent, and http client types let an agent use the identical collection-and-document tools from a quick prototype all the way to a Chroma Cloud deployment, with no managed cost until you opt into the cloud. In short: Pinecone if you prefer managed scale and built-in embeddings; Chroma if you prefer open-source control, zero-cost self-hosting, and a smooth path from prototype to cloud.

FAQ

Do both servers run locally?: Both MCP servers run locally over stdio — Pinecone's via npx (@pinecone-database/mcp) and Chroma's via uvx (chroma-mcp) — but they connect to different backends. Pinecone always talks to its managed cloud with a PINECONE_API_KEY, while Chroma connects to a backend you choose: in-memory, on-disk, a self-hosted http server, or Chroma Cloud.
Which handles embeddings for me?: Pinecone does, through integrated inference: create-index-for-model embeds text automatically on upsert and search. With Chroma you supply embeddings or configure external embedding-provider keys, so the embedding step is something you wire up rather than a built-in default.
Can either be self-hosted for free?: Chroma can — it is open source and runs free in ephemeral, persistent, or http (self-hosted server) mode; only Chroma Cloud is paid. Pinecone is a managed cloud service with a free starter tier and paid plans, not something you self-host.