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Glanser Guidelines Server

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Provides semantic search over a team's coding guidelines corpus using FastMCP, ChromaDB, and sentence-transformers. Enables fully offline operation with tools f

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About

Provides semantic search over a team's coding guidelines corpus using FastMCP, ChromaDB, and sentence-transformers. Enables fully offline operation with tools for searching, browsing, and filtering guidelines by scope.

README

Semantic search over the team's coding guidelines corpus. Powered by FastMCP + ChromaDB + sentence-transformers (all-MiniLM-L6-v2). 100% free — no API keys, no external services, runs fully offline after setup.


Folder Structure

mcp-server/
├── server.py          ← MCP server (run this on the host)
├── ingest.py          ← One-time ingestion script
├── requirements.txt   ← Python dependencies
├── documents/         ← Drop your .md guideline files here
│   └── CODING_GUIDELINES.md
└── chroma_db/         ← Created automatically by ingest.py (do not edit)

Setup (run once on the host machine)

1. Install dependencies

pip install -r requirements.txt

sentence-transformers will download the all-MiniLM-L6-v2 model (~80 MB) on first run and cache it. Subsequent runs are fully offline.

2. Add your documents

Copy markdown files into the documents/ folder:

cp /path/to/CODING_GUIDELINES.md documents/

3. Ingest (embed once, saved to disk)

python ingest.py

This reads every .md file in documents/, embeds each section, and persists the vectors to chroma_db/. You only re-run this when adding a new document.

Useful flags:

python ingest.py --file documents/NEW_DOC.md   # add a single new doc
python ingest.py --reset                        # wipe and re-ingest everything
python ingest.py --list                         # see what is currently indexed

4. Start the server

python server.py

Server starts on http://0.0.0.0:8000.


Hosting (team access)

Deploy to Railway or Render (both have free tiers):

  1. Push this mcp-server/ folder to a git repo
  2. Create a new service pointing to that repo
  3. Set start command: python server.py
  4. Mount a persistent volume at /app/chroma_db (so embeddings survive deploys)
  5. Run python ingest.py once via the host console after deploy

Railway/Render automatically provision an HTTPS URL like: https://glanser-guidelines-mcp.railway.app


Team .mcp.json entry

Each team member adds this to their .mcp.json:

{
  "mcpServers": {
    "coding-guidelines": {
      "type": "http",
      "url": "https://your-hosted-domain.com/mcp"
    }
  }
}

Available Tools

Tool What it does
search_guidelines Semantic search across all docs — use this first
get_section Fetch full content of a specific section
list_sections Browse all section titles across the corpus
get_by_scope Filter rules by library, client, or both
list_documents See all indexed documents and their section counts

Adding a New Document

# 1. Copy the new doc
cp NEW_GUIDELINES.md documents/

# 2. Ingest only the new file (does not re-embed existing docs)
python ingest.py --file documents/NEW_GUIDELINES.md

# 3. No server restart needed — ChromaDB is queried live

Local dev / testing (without hosting)

{
  "mcpServers": {
    "coding-guidelines": {
      "type": "http",
      "url": "http://localhost:8000/mcp"
    }
  }
}

from github.com/Vbridge7/MCP-server

Installing Glanser Guidelines Server

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/Vbridge7/MCP-server

FAQ

Is Glanser Guidelines Server MCP free?

Yes, Glanser Guidelines Server MCP is free — one-click install via Unyly at no cost.

Does Glanser Guidelines Server need an API key?

No, Glanser Guidelines Server runs without API keys or environment variables.

Is Glanser Guidelines Server hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Glanser Guidelines Server in Claude Desktop, Claude Code or Cursor?

Open Glanser Guidelines Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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