About docs-mcp
docs-mcp turns Word, Excel, PDF, and PowerPoint files into a searchable vector store for agents that need to retrieve document content. Vision-model extraction covers scanned pages, charts, and tables, and search results include page numbers.
Key features
- 01Ingests multiple office document formats
- 02Extracts page content with a vision model
- 03Searches document chunks semantically
- 04Includes page numbers in results
- 05Manages documents and credit balance
Use cases
- 01Search content in scanned files
- 02Find details in tables or charts
- 03Cite page numbers in answers
MCP support
It exposes tools to MCP clients for uploading, listing, checking, searching, and deleting documents.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://docs.regiq.in/api/mcpclaude mcp add --transport http shreyas-profile-docs https://docs.regiq.in/api/mcp{"mcpServers":{"shreyas-profile-docs":{"type":"http","url":"https://docs.regiq.in/api/mcp"}}}Open in Cursor{"servers":{"shreyas-profile-docs":{"type":"http","url":"https://docs.regiq.in/api/mcp"}}}Open in VS Code{"mcpServers":{"shreyas-profile-docs":{"type":"http","url":"https://docs.regiq.in/api/mcp"}}}{"mcpServers":{"shreyas-profile-docs":{"serverUrl":"https://docs.regiq.in/api/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://docs.regiq.in/api/mcpAuth requiredTools
Details
From the project READMEdocs-mcp
Drop any Word, Excel, PDF or PowerPoint into a vector RAG store. Vision-model extraction handles scans, charts, and tables. Every returned chunk carries its page number for precise citations. Priced at exact break-even via Stripe — we make $0 per credit sold.
Live: docs.regiq.in
What it does
- Ingest — accepts
.pdf,.docx,.xlsx,.pptx,.doc,.xls,.pptup to 50 MB. - Extract — renders every page as an image, runs Google Gemini 2.5 Flash Lite (via OpenRouter) over each page. Text, tables, and figure descriptions come out verbatim.
- Store — chunks (~500 tokens, 50-token overlap), embeds via
openai/text-embedding-3-small(1536 dims), stored in Postgres + pgvector with page-number metadata. - Retrieve — cosine-similarity search returns the top-k chunks; your agent synthesizes the answer.
Tools
| Tool | What it does |
|---|---|
docs_upload({filename, contentBase64, mimeType?}) | Small (≤~7 MB) programmatic upload. Ingest runs async. |
docs_list() | All documents owned by the calling key. |
docs_get({id}) | One doc's metadata + status + chunk count. |
docs_search({query, k?, documentIds?}) | Semantic search. Returns top-k chunks with page numbers. Free. |
docs_delete({id}) | Permanent delete. |
docs_balance() | Credit balance + last 10 transactions. |
Bigger files: upload via the web dashboard at docs.regiq.in/dashboard (max 50 MB).
Pricing
1 credit = 1 page ingested. Queries are free. New accounts get 100 pages free on sign-up.
| Top-up | Pages you get | ~Docs (10-pg avg) |
|---|---|---|
| $5 | 5,700 | 570 |
| $10 | 11,700 | 1,170 |
| $20 | 23,900 | 2,390 |
| $50 | 60,500 | 6,050 |
Per-page underlying cost is roughly $0.0005 vision + $0.00003 embedding via OpenRouter. Prices are set at exact break-even after Stripe's 2.9% + $0.30 fee — that flat fee is why $2 top-ups aren't offered (18% of $2 evaporates to Stripe).
Setup — any MCP client
- Sign in at docs.regiq.in with Google or GitHub.
- Copy your API key from
/dashboard. - Add to your client config:
{
"mcpServers": {
"docs": {
"url": "https://docs.regiq.in/api/mcp",
"headers": {
"Authorization": "Bearer docs_live_..."
}
}
}
}
Works in Claude Desktop, Cursor, Zed, and anything else that speaks streamable-http MCP.
Recommended flow
1. docs_upload({filename, contentBase64}) → { id, status: "processing" }
2. poll docs_get({id}) until status="ready" (~10-60s for 10 pages)
3. docs_search({query: "...", k: 8}) → chunks with page numbers
4. Your LLM synthesizes an answer and cites the page numbers.
Self-host
git clone https://github.com/globalion/docs-mcp
cd docs-mcp
cp .env.example .env # fill in Google OAuth + OpenRouter + (optional) Stripe
docker compose up -d --build
Uses pgvector/pgvector:pg16 image so the vector extension is pre-installed. docker exec docs-mcp-web npx [email protected] db push --accept-data-loss --skip-generate on first boot to sync the schema (the container CMD does this automatically).
License
Comments
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