KMCP

agent-accessibility12starsClaim this server

Open-source MCP server for your docs. Zero LLM at query time. docker compose up and go.

Pasang Jalankan di PlugMCPClaim this server

1# KMCP

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Tambahkan server ini

Install from the publisher. Not a PlugMCP endpoint.

Jalankan di PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Jalankan di PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Buka

Server facts

Local

Transport: stdio
License: AGPL-3.0
Last checked: 2026-10-27

Stars: 12
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install KMCP?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does KMCP need an API key?

No required environment variable is listed on this record.

What transport does KMCP use?

KMCP runs locally over stdio.

When was KMCP last checked?

Last checked 2026-10-27. Open-source MCP server for your docs. Zero LLM at query time. docker compose up and go.

From the publisher

Documentation

KnowledgeMCP

Give your docs an MCP endpoint. Every AI agent can use them.

https://github.com/user-attachments/assets/304fa31a-5138-4d02-b407-4c518f6a4145

KnowledgeMCP turns any documentation source (websites, PDFs, Confluence, Notion, S3, GitHub) into a standards-compliant Model Context Protocol (MCP) endpoint. Claude, GitHub Copilot, Cursor, and any other MCP-compatible agent can search and read those docs instantly — with no LLM calls at query time (we use a tiny local embedding model + hybrid BM25/kNN search in OpenSearch).

🔌 MCP-native — three tools (docs_search, code_sample_search, docs_fetch) any agent can plug into
💰 Zero-cost query path — local embeddings + OpenSearch hybrid search. No OpenAI/Bedrock fees per query.
🐳 docker compose up works — runs fully local, no AWS account, no credit card
☁️ Production-ready AWS path when you want it — Lambda + DynamoDB + SQS + S3 + managed OpenSearch via the bundled SAM template

Quick start

git clone https://github.com/hashwnath/KMCP.git
cd KMCP
make up                # docker compose up -d --build

Then:

Dashboard → http://localhost:3000 (signup → add a source → search)
Admin REST API → http://localhost:8081
MCP endpoint → http://localhost:8000/mcp/{your-tenant-slug}

First-time start downloads the fastembed model (~30 MB) and OpenSearch (~700 MB image).

How agents use it

Point any MCP client at your tenant URL:

{
  "mcpServers": {
    "MyDocs": {
      "url": "http://localhost:8000/mcp/your-tenant-slug",
      "type": "http"
    }
  }
}

The agent gets three tools:

Tool	Purpose	Returns
`docs_search`	semantic + keyword search	up to 10 chunks with title, URL, ~500-token excerpt
`code_sample_search`	code-specific search with optional language filter	up to 20 snippets with language + context
`docs_fetch`	full page content	clean markdown

Architecture

┌────────────────────────────────────────────────────────────┐
│   AI Agents  (Claude, Cursor, Copilot, Continue, ...)      │
└──────────────────────────┬─────────────────────────────────┘
                           │ POST /mcp/{tenant_slug}
┌──────────────────────────▼─────────────────────────────────┐
│   MCP Server (FastMCP)  — docs_search / code_search / fetch │
└──────────────────────────┬─────────────────────────────────┘
            ┌──────────────┼──────────────┐
            ▼              ▼              ▼
    ┌───────────────┐ ┌──────────┐ ┌──────────────┐
    │   OpenSearch  │ │  SQLite  │ │  Filesystem  │
    │ (BM25 + kNN)  │ │ tenants  │ │  blobs       │
    │  ~768 token   │ │ sources  │ │  uploads     │
    │  chunks       │ │ jobs     │ │              │
    └───────────────┘ └──────────┘ └──────────────┘
                           ▲
┌──────────────────────────┴─────────────────────────────────┐
│ Admin API (Starlette)  +  Background Worker                 │
│   signup/login (JWT)        crawl → markdown → chunk →      │
│   sources CRUD              embed → OpenSearch              │
│   analytics                                                 │
└────────────────────────────────────────────────────────────┘

(In AWS mode, swap SQLite → DynamoDB, Filesystem → S3, the worker queue → SQS, and run each service as its own Lambda. The application code is unchanged because every AWS call routes through src/common/backends/.)

Supported source types

Type	What it ingests
`website_url`	Full sitemap crawl → markdown
`paste_text`	Inline text
`file_upload`	PDF, DOCX, PPTX, MD, HTML, TXT
`cloud_storage`	S3, Azure Blob, GCS
`wiki_kb`	Confluence, Notion, SharePoint, GitBook
`git_repo`	Public or private GitHub/GitLab repos (token optional)

Configuration

Defaults work for local docker-compose. To customise, copy .env.example to .env and edit. The most useful knobs:

Var	Default	Notes
`BACKEND`	`local`	`local` (default) or `aws`
`EMBEDDING_PROVIDER`	`local`	`local` (fastembed) / `bedrock` / `openai`
`LOCAL_EMBEDDING_MODEL`	`BAAI/bge-small-en-v1.5`	Any fastembed-supported model
`OPENSEARCH_ENDPOINT`	`http://opensearch:9200`	In compose; override for hosted OpenSearch
`MAX_DOCS_PER_TENANT`	`500`	Per-tenant quota
`RATE_LIMIT_PER_SECOND`	`10`	MCP endpoint rate limit (per tenant)

AWS production deployment

See docs/AWS_DEPLOYMENT.md for the SAM template (Lambda + DynamoDB + SQS + S3 + OpenSearch + SES), cost estimate, and operational runbook.

Contributing

PRs welcome. See CONTRIBUTING.md for the codebase tour and local dev setup.

make test        # full pytest suite (BACKEND=local)
make test-aws    # AWS-mocked suite
make up          # docker compose up -d --build

License

Backend (src/, infra/, top-level configs) — AGPL-3.0
Frontend (frontend/) — MIT

The AGPL-3.0 license means hosted/SaaS use must publish modifications under the same license. If that's a problem for your use case, please open an issue so we can discuss commercial licensing.

Why KnowledgeMCP?

	KnowledgeMCP	Typical RAG tools
Query cost	$0 (local embeddings + OpenSearch)	$0.01-0.10/query (LLM reranking)
Agent integration	Native MCP — plug and play	REST API + custom glue code
Self-hosted	`docker compose up`, no cloud account	Usually needs cloud APIs
Multi-tenant	Per-tenant isolation built-in	Single-tenant, bolt-on later
Latency	~100ms (no LLM in path)	1-5s (LLM reranking)

Community

GitHub Discussions — questions, ideas, show-and-tell
Issues — bug reports, feature requests

Acknowledgements

FastMCP — the MCP server framework
fastembed — ONNX-runtime embedding library
OpenSearch — hybrid BM25 + kNN search
Microsoft Learn MCP server team — for documenting hard-earned lessons that shaped the tenant-context-via-middleware design

KMCP

agent-accessibility12starsClaim this server

Open-source MCP server for your docs. Zero LLM at query time. docker compose up and go.

Devops Knowledge Memory

Pasang Jalankan di PlugMCPClaim this server

GitHub Website

Jalankan di PlugMCP

1# KMCP

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Tambahkan server ini

Install from the publisher. Not a PlugMCP endpoint.

Jalankan di PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Jalankan di PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Buka

Server facts

Local

Transport: stdio
License: AGPL-3.0
Last checked: 2026-10-27

Stars: 12
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install KMCP?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does KMCP need an API key?

No required environment variable is listed on this record.

What transport does KMCP use?

KMCP runs locally over stdio.

When was KMCP last checked?

Last checked 2026-10-27. Open-source MCP server for your docs. Zero LLM at query time. docker compose up and go.

From the publisher

Documentation

KnowledgeMCP

Give your docs an MCP endpoint. Every AI agent can use them.

https://github.com/user-attachments/assets/304fa31a-5138-4d02-b407-4c518f6a4145

🔌 MCP-native — three tools (docs_search, code_sample_search, docs_fetch) any agent can plug into
💰 Zero-cost query path — local embeddings + OpenSearch hybrid search. No OpenAI/Bedrock fees per query.
🐳 docker compose up works — runs fully local, no AWS account, no credit card
☁️ Production-ready AWS path when you want it — Lambda + DynamoDB + SQS + S3 + managed OpenSearch via the bundled SAM template

Quick start

git clone https://github.com/hashwnath/KMCP.git
cd KMCP
make up                # docker compose up -d --build

Then:

Dashboard → http://localhost:3000 (signup → add a source → search)
Admin REST API → http://localhost:8081
MCP endpoint → http://localhost:8000/mcp/{your-tenant-slug}

First-time start downloads the fastembed model (~30 MB) and OpenSearch (~700 MB image).

How agents use it

Point any MCP client at your tenant URL:

{
  "mcpServers": {
    "MyDocs": {
      "url": "http://localhost:8000/mcp/your-tenant-slug",
      "type": "http"
    }
  }
}

The agent gets three tools:

Tool	Purpose	Returns
`docs_search`	semantic + keyword search	up to 10 chunks with title, URL, ~500-token excerpt
`code_sample_search`	code-specific search with optional language filter	up to 20 snippets with language + context
`docs_fetch`	full page content	clean markdown

Architecture

┌────────────────────────────────────────────────────────────┐
│   AI Agents  (Claude, Cursor, Copilot, Continue, ...)      │
└──────────────────────────┬─────────────────────────────────┘
                           │ POST /mcp/{tenant_slug}
┌──────────────────────────▼─────────────────────────────────┐
│   MCP Server (FastMCP)  — docs_search / code_search / fetch │
└──────────────────────────┬─────────────────────────────────┘
            ┌──────────────┼──────────────┐
            ▼              ▼              ▼
    ┌───────────────┐ ┌──────────┐ ┌──────────────┐
    │   OpenSearch  │ │  SQLite  │ │  Filesystem  │
    │ (BM25 + kNN)  │ │ tenants  │ │  blobs       │
    │  ~768 token   │ │ sources  │ │  uploads     │
    │  chunks       │ │ jobs     │ │              │
    └───────────────┘ └──────────┘ └──────────────┘
                           ▲
┌──────────────────────────┴─────────────────────────────────┐
│ Admin API (Starlette)  +  Background Worker                 │
│   signup/login (JWT)        crawl → markdown → chunk →      │
│   sources CRUD              embed → OpenSearch              │
│   analytics                                                 │
└────────────────────────────────────────────────────────────┘

Supported source types

Type	What it ingests
`website_url`	Full sitemap crawl → markdown
`paste_text`	Inline text
`file_upload`	PDF, DOCX, PPTX, MD, HTML, TXT
`cloud_storage`	S3, Azure Blob, GCS
`wiki_kb`	Confluence, Notion, SharePoint, GitBook
`git_repo`	Public or private GitHub/GitLab repos (token optional)

Configuration

Defaults work for local docker-compose. To customise, copy .env.example to .env and edit. The most useful knobs:

Var	Default	Notes
`BACKEND`	`local`	`local` (default) or `aws`
`EMBEDDING_PROVIDER`	`local`	`local` (fastembed) / `bedrock` / `openai`
`LOCAL_EMBEDDING_MODEL`	`BAAI/bge-small-en-v1.5`	Any fastembed-supported model
`OPENSEARCH_ENDPOINT`	`http://opensearch:9200`	In compose; override for hosted OpenSearch
`MAX_DOCS_PER_TENANT`	`500`	Per-tenant quota
`RATE_LIMIT_PER_SECOND`	`10`	MCP endpoint rate limit (per tenant)

AWS production deployment

See docs/AWS_DEPLOYMENT.md for the SAM template (Lambda + DynamoDB + SQS + S3 + OpenSearch + SES), cost estimate, and operational runbook.

Contributing

PRs welcome. See CONTRIBUTING.md for the codebase tour and local dev setup.

make test        # full pytest suite (BACKEND=local)
make test-aws    # AWS-mocked suite
make up          # docker compose up -d --build

License

Backend (src/, infra/, top-level configs) — AGPL-3.0
Frontend (frontend/) — MIT

The AGPL-3.0 license means hosted/SaaS use must publish modifications under the same license. If that's a problem for your use case, please open an issue so we can discuss commercial licensing.

Why KnowledgeMCP?

	KnowledgeMCP	Typical RAG tools
Query cost	$0 (local embeddings + OpenSearch)	$0.01-0.10/query (LLM reranking)
Agent integration	Native MCP — plug and play	REST API + custom glue code
Self-hosted	`docker compose up`, no cloud account	Usually needs cloud APIs
Multi-tenant	Per-tenant isolation built-in	Single-tenant, bolt-on later
Latency	~100ms (no LLM in path)	1-5s (LLM reranking)

Community

GitHub Discussions — questions, ideas, show-and-tell
Issues — bug reports, feature requests

Acknowledgements

FastMCP — the MCP server framework
fastembed — ONNX-runtime embedding library
OpenSearch — hybrid BM25 + kNN search
Microsoft Learn MCP server team — for documenting hard-earned lessons that shaped the tenant-context-via-middleware design