About negotiate-mcp
An MCP server that lets AI shoppers negotiate with stores implementing negotiate.v1. It provides a consistent set of tools for discovering stores and products, conducting negotiation sessions, and reading their history.
Key features
- 01Check store protocol support
- 02List negotiable products
- 03Start merchant chat sessions
- 04Send shopper messages
- 05Read negotiation history
Use cases
- 01Find stores that support negotiate.v1
- 02Browse products available for negotiation
- 03Negotiate a product’s price with a store
- 04Review an ongoing negotiation
MCP support
Exposes five negotiation tools to MCP clients, including Claude Desktop, Cowork, and Claude Code. The same tools work with any negotiate.v1-compliant store.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEnegotiate-mcp
Model Context Protocol (MCP) server for the negotiate.v1 protocol. Once installed in Claude Desktop, Cowork, Claude Code, or any other MCP-aware client, your Claude gains five native tools for negotiating with any negotiate.v1-compliant store.
What you get
| Tool | Purpose |
|---|---|
discover_store(domain) | Probe a domain to check if it's negotiable. Returns the protocol descriptor. |
list_products(domain) | Enumerate negotiable products at the store. |
start_negotiation(domain, product_id) | Open a chat session with the merchant agent. |
send_message(next_url, message) | Send one shopper turn. |
read_history(history_url) | Read the running history of a session. |
The agent uses these like a human would use a browser: discover the store, pick a product, start a chat, send turns until the deal closes.
mcp-name: io.github.sanjana-pier39/negotiate-mcp
Install
The recommended path uses uv — no virtualenv plumbing, picks the right Python automatically.
# install uv if you don't have it (macOS):
brew install uv
# then point Claude Desktop / Cowork / Claude Code at it (see below).
# uvx will install the package the first time it's invoked.
If you'd rather use plain pip:
pip install negotiate-mcp
Wire it into Claude Desktop
-
Open your Claude Desktop config:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
-
Add this entry under
mcpServers(creating the file if it doesn't exist):{ "mcpServers": { "negotiate-agent": { "command": "uvx", "args": ["negotiate-mcp"] } } } -
Quit and re-open Claude Desktop. The five tools should appear in any new conversation.
If you installed with plain pip instead of uv, replace the command/args block with:
"command": "negotiate-mcp",
"args": []
Wire it into Cowork or Claude Code
Same negotiate-mcp command. Add it to the corresponding MCP config in those clients (consult their docs for exact paths). The tool surface is identical.
Try it
Once installed, in a fresh chat:
Negotiate for a Dyson HP07 at negotiate.pier39.ai. Try to get it under $500. Bonus points for the engraved gift box.
Claude will call discover_store("negotiate.pier39.ai"), find the HP07 in the product list, call start_negotiation, then drive the conversation through send_message until closed: true. No prompt acrobatics needed.
Test standalone (no Claude required)
# Run the server on stdio:
uvx negotiate-mcp
# Or, if you've used pip:
python -m negotiate_mcp
Most useful when paired with the mcp CLI to inspect tool definitions and exercise them by hand.
Adding more stores
The connector works against any negotiate.v1-compliant store, not just the Atlas reference (negotiate.pier39.ai). As stores adopt the protocol, just point your shopper agent at their domain — the same five tools work everywhere.
See PROTOCOL.md for the full spec.
Develop locally
git clone https://github.com/sanjana-pier39/negotiate-mcp
cd negotiate-mcp
pip install -e .
python -m negotiate_mcp # runs on stdio
To publish a new version, see PUBLISH.md.
License
MIT.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.