Proxenio MCP Server
Enables AI agents to discover and interact with Proxenio's verified intent network for professional matching, including viewing matches and accepting introductions.
README
Proxenio MCP Server
MCP (Model Context Protocol) server for the Proxenio verified intent network. Enables AI agents running in Claude Desktop, Cursor, VS Code, and other MCP-compatible clients to discover and interact with Proxenio's professional matching engine.
What It Does
This server gives your AI agent four tools:
| Tool | What it does |
|---|---|
proxenio_discover |
Learn about the platform, trust model, and API — no auth required |
proxenio_set_api_key |
Configure your Proxenio API key for authentication |
proxenio_get_matches |
Read your principal's verified professional matches |
proxenio_accept_match |
Accept an introduction request, creating a deal |
Your agent inherits the human principal's trust tier. It sees exactly what the principal sees — same matching engine, same rules, same verification gates. No shortcuts.
Prerequisites
- Node.js 18+
- A Proxenio account with a verified email and completed profile
- An API key generated at proxenio.ai/agents
Installation
npx @proxenio-tech/mcp-server
Usage with Claude Desktop
Add to your Claude Desktop configuration (claude_desktop_config.json):
{
"mcpServers": {
"proxenio": {
"command": "npx",
"args": ["@proxenio-tech/mcp-server"]
}
}
}
Then in Claude Desktop, you can say:
"What is Proxenio?"
→ Claude usesproxenio_discoverautomatically
"Connect to Proxenio with this key: prx_YOUR_KEY_HERE_________________"
→ Claude usesproxenio_set_api_key
"Show me my professional matches"
→ Claude usesproxenio_get_matches
"Accept the introduction from Maria Georgiou"
→ Claude usesproxenio_accept_match
Usage with Cursor
Add to your Cursor MCP settings:
{
"proxenio": {
"command": "npx",
"args": ["@proxenio-tech/mcp-server"]
}
}
Remote Deployment (HTTP)
For multi-client or cloud deployment:
TRANSPORT=http PORT=3001 node dist/index.js
The server exposes:
POST /mcp— MCP protocol endpointGET /health— Health check
Tools Reference
proxenio_discover
No authentication required. Returns platform info, trust model, capabilities, and links.
proxenio_set_api_key
| Parameter | Type | Required | Description |
|---|---|---|---|
api_key |
string | Yes | Full API key (36 chars, starts with prx_) |
proxenio_get_matches
| Parameter | Type | Default | Description |
|---|---|---|---|
filter_type |
all|top|high|standard |
all |
Filter by match quality |
filter_status |
all|pending|accepted |
all |
Filter by status |
min_score |
number (40-100) | 40 |
Minimum match score |
Returns: Principal info, matches with counterparty profiles, trust tiers, scores, and rate limit status.
proxenio_accept_match
| Parameter | Type | Required | Description |
|---|---|---|---|
match_id |
string (UUID) | Yes | Match ID from proxenio_get_matches |
Returns: Confirmation, counterparty details, new deal ID, rate limit status.
Guard rails: Principal must be the receiving party. Cannot accept own requests. Match must be active with a pending intro.
Trust Model
- Agents inherit their human principal's trust tier at request time
- Trust tiers: 0 (Unverified) → 1 (Starter) → 2 (Active) → 3 (Trusted) → 4 (Proven)
- All engine verification gates apply — agents cannot bypass any
- Counterparties see transparency badge:
🤖 AI Agent active on behalf of [Name] - Only humans can log outcomes and confirm deals
Rate Limits
- 60 requests/hour per API key
- 3 keys maximum per user (= 180 requests/hour total)
- Rate limit headers included in all responses
Security
- API keys are never logged or stored by the MCP server
- Keys are validated on format before use (prefix, length)
- All communication uses HTTPS
- The MCP server acts as a pass-through — no data is cached
Links
- Platform: proxenio.ai
- Agent Docs: proxenio.ai/agents/docs
- Discovery Manifest: .well-known/proxenio.json
- OpenAPI Spec: api/agent/openapi.json
License
MIT — Proxenio Technologies Ltd
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.