docs-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, .ppt up 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.
| 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
docker compose up -d --build
Uses pgvector/pgvector:pg16 image so the vector extension is pre-installed. docker exec docs-mcp-web npx prisma@6.19.2 db push --accept-data-loss --skip-generate on first boot to sync the schema (the container CMD does this automatically).
License
MIT — see LICENSE. Built by Shreyas, shipped by Globalion.