Quotations MCP Server

Standalone MCP server exposing the quotations-app backend as tools. It's a thin HTTP client over the quotations REST API — no database of its own — so it stays decoupled and can point at local dev or the live Render backend.

MCP agent ──MCP──► server.py ──HTTP──► quotations-app backend ──► MongoDB

Tools

Purpose is conversational intelligence — let an agent answer natural-language questions about quotations (counts, values, who-has-what, lookups) and take actions.

Conversational / query (read):

Tool	Answers
quotation_stats()	"how many are pending?", "total pipeline value?", "who has the most?" — counts by status + value by assignee
search_quotations(company?, status?, assignee?, number?, min_total?, max_total?)	"show quotations assigned to Vijender over ₹10k" — filtered list + total value
find_by_number(quotation_number)	resolves a human number like QT-2026-000005 to the full quotation
list_quotations()	all quotations (compact)
get_quotation(quotation_id)	one full quotation by internal id
health()	backend reachability + count

READ-ONLY by design. This MCP only queries the customer's data and answers questions — it never writes (no create/reassign). Creating or modifying quotations is the customer app's job. The backend exposes only list + get, so filtering/aggregation is done here; prices/totals come only from the server-computed data — never invented.

Completion / status

A quotation is "completed" only if the customer's data stores that state. Today their backend hard-codes status:"draft" and never changes it, so quotation_stats / search_quotations(status=...) will only ever report draft. The moment their app writes a real status (e.g. completed/sent), these read tools surface it automatically — no change here.

Install

pip install -r requirements.txt   # mcp[cli], httpx

Run

# stdio (dev / desktop MCP clients)
python server.py

# HTTP endpoint (for the MCP agent to connect to)
MCP_TRANSPORT=http MCP_PORT=8200 python server.py
# → MCP endpoint at http://<host>:8200/mcp

# inspect/try tools
mcp dev server.py

Env

Var	Default	Purpose
QUOTATIONS_API_URL	https://quotations-app.onrender.com	backend base URL
QUOTATIONS_TIMEOUT	30	HTTP timeout (bump for Render cold start ~50s)
MCP_TRANSPORT	stdio	stdio or http
MCP_HOST / MCP_PORT	127.0.0.1 / 8200	bind for http transport

Notes

• Deployed separately from the quotations backend and from Oscar.
• The Oscar agent will later connect to this server (as an MCP client) via a new endpoint — this repo/folder does not depend on Oscar.