How do I use Proxenio MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Proxenio MCP Server Show me my professional matches" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Proxenio MCP Server

Official

by proxenio

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

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.

Related MCP server: m3x-mcp-server

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 uses proxenio_discover automatically

"Connect to Proxenio with this key: prx_YOUR_KEY_HERE_________________"
→ Claude uses proxenio_set_api_key

"Show me my professional matches"
→ Claude uses proxenio_get_matches

"Accept the introduction from Maria Georgiou"
→ Claude uses proxenio_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 endpoint
GET /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

License

MIT — Proxenio Technologies Ltd

Available Tools

4 tools

proxenio_accept_matchAccept Proxenio IntroductionA

Accept an introduction request on behalf of the human principal.

This creates a deal between the principal and the counterparty. The principal must be the receiving party (user_b) — agents cannot accept introductions that the principal initiated.

IMPORTANT: This is an action with real consequences. It connects two professionals and creates a deal container. Only accept matches that align with the principal's stated intent.

Requires: API key must be set via proxenio_set_api_key first.

Args:

match_id (string, UUID): The match ID to accept. Get this from proxenio_get_matches results.

Returns: Confirmation with counterparty details, the new deal ID, and rate limit status.

Guard rails enforced by the API:

Principal must be a participant in the match
Principal must be the receiving party (user_b), not the requester
Match must have an active status
An introduction request must exist and be in pending/awaiting_consent state
Agent cannot accept the principal's own outgoing requests

Examples:

Use when: Principal wants to accept a specific pending introduction
Use when: Agent decides a match aligns with principal's intent and should be accepted
Don't use when: You haven't checked the match details first (use proxenio_get_matches)
Don't use when: The match was initiated by the principal (agent can only accept incoming)

Error Handling:

400: Match not in correct state, no intro request exists
403: Principal is not authorized (e.g., they are the requester, not receiver)
404: Match ID not found
429: Rate limit exceeded

ParametersJSON Schema

Name	Required	Description	Default
`match_id`	Yes	UUID of the match to accept. Get this from proxenio_get_matches. The principal must be the receiving party (user_b), not the requester.

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only indicate non-read-only and non-destructive, but the description adds critical behavioral context: it creates a deal container, has 'real consequences', connects professionals, and enforces guard rails (principal must be user_b, match must be active, etc.). This goes well beyond the structured annotations and fully informs the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but well-organized into sections (args, returns, guard rails, examples, error handling). It is front-loaded with the core purpose. While every section earns its place, it could be tightened slightly without losing important nuance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description appropriately details the return value (confirmation with counterparty details, deal ID, rate limit status). It covers preconditions, API guard rails, and error codes, making it fully complete for an agent to understand the tool's behavior and consequences.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of the parameter and already includes a description. The tool description adds extra value by directing the agent to get the match_id from proxenio_get_matches and reinforcing the user_b constraint, but the schema already conveys the core semantics, so the incremental value is moderate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource: 'Accept an introduction request on behalf of the human principal' and explains the resulting action ('creates a deal'). It clearly distinguishes from sibling tools like proxenio_get_matches (fetching) and proxenio_set_api_key (configuration).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use when' and 'Don't use when' examples, mentions the prerequisite of setting an API key, and points to proxenio_get_matches as the source for match IDs. This gives strong guidance on when to use the tool and when to avoid it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

proxenio_discoverDiscover Proxenio PlatformA

Read-onlyIdempotent

Get information about the Proxenio platform and its agent API.

Proxenio is a verified intent network for professional deal-making. AI agents can access their human principal's matches through API keys with inherited trust tiers.

This tool requires no authentication. Use it to understand the platform before connecting.

Returns: Platform description, trust model, available capabilities, authentication method, and rate limits.

Examples:

Use when: "What is Proxenio?" or "How do I connect to Proxenio?"
Use when: Agent needs to understand what Proxenio offers before authenticating
Don't use when: You already know about Proxenio and just need to read matches

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that 'This tool requires no authentication' and lists return contents (platform description, trust model, available capabilities, authentication method, rate limits). Since annotations already declare readOnly/idempotent/non-destructive, the added no-auth and return-value details are valuable supplementary context, though it does not dive deeper into edge behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and organized with a concise opening, background sentence, return list, and examples. It is slightly longer than strictly necessary due to repeated 'before connecting/authenticating' phrasing, but every section adds useful orientation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple discovery tool with no parameters and strong annotations, the description is complete: it states purpose, no-auth requirement, returned information, and usage examples. It also clearly signals when not to use it by referencing reading matches, which maps to the sibling proxenio_get_matches.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the empty schema fully covers parameter semantics. The description appropriately adds that no authentication is required, but there are no parameter details to document; this matches the baseline of 4 for a zero-param tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence clearly states the tool's function: 'Get information about the Proxenio platform and its agent API.' This distinguishes it from siblings like proxenio_get_matches (reading matches) and proxenio_set_api_key (authentication setup), making the purpose specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit usage guidance is provided: 'Use it to understand the platform before connecting,' plus concrete example triggers ('What is Proxenio?') and a negative case ('Don't use when you already know about Proxenio and just need to read matches'), which points toward the alternative sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

proxenio_get_matchesGet Proxenio MatchesA

Read-onlyIdempotent

Read the principal's verified professional matches from Proxenio.

Returns matches sorted by match score (descending). Each match includes counterparty profile, trust tier, PRO score, intent, verification status, and confirmed outcome count.

Requires: API key must be set via proxenio_set_api_key first.

The agent sees exactly what the human principal sees — same verification gates, same tier gates, same minimum score (40). Matches below 40 are never returned.

Args:

filter_type ('all' | 'top' | 'high' | 'standard'): Filter by match quality tier (default: 'all')
filter_status ('all' | 'pending' | 'accepted'): Filter by match status (default: 'all')
min_score (number, 40-100): Minimum match score threshold (default: 40)

Returns: Principal info, list of matches with full counterparty profiles, trust signals, and rate limit status.

Examples:

Use when: "Show me my matches" or "What professional connections are available?"
Use when: "Find my best matches" -> use filter_type='top'
Use when: "Which introductions are pending?" -> use filter_status='pending'
Don't use when: API key has not been set yet (use proxenio_set_api_key first)

Error Handling:

Returns auth error if API key is invalid or revoked
Returns rate limit error if 60 requests/hour exceeded
Returns empty list if principal has no matches (profile may be incomplete)

ParametersJSON Schema

Name	Required	Description	Default
`min_score`	No	Minimum match score to include (40-100). Default: 40
`filter_type`	No	Filter matches by type: 'all', 'top', 'high', or 'standard'	all
`filter_status`	No	Filter matches by status: 'all', 'pending', or 'accepted'	all

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds critical behavior: sorting by match score descending, the hard minimum score of 40, the fact that the agent sees exactly what the principal sees, and specific error outcomes (auth error, rate limit, empty list). This is rich contextual disclosure that aids correct invocation and interpretation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Requires, Args, Returns, Examples, Error Handling) and front-loads the core action. It is slightly repetitive (match contents described twice) and could be trimmed, but every section serves a purpose and the organization aids scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has three optional params and no output schema, the description is remarkably complete: it explains prerequisites, filtering semantics, sort order, visibility constraints, return contents, and error scenarios. An agent would have enough context to select and call this tool correctly without external documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers all three parameters with 100% description coverage, so baseline is 3. The description adds value by re-listing args with user-friendly explanations (e.g., 'Filter by match quality tier') and tying them to example queries ('Find my best matches' -> filter_type='top'). This goes slightly beyond the schema but does not introduce entirely new semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Read the principal's verified professional matches from Proxenio.' This clearly distinguishes it from siblings like proxenio_discover (finding new matches) and proxenio_accept_match (acting on matches). The purpose is unambiguous and immediately comprehensible.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage context with 'Use when' examples and a prerequisite ('Requires: API key must be set via proxenio_set_api_key first'). It also says 'Don't use when: API key has not been set yet.' However, it does not explicitly contrast with alternatives like proxenio_discover or proxenio_accept_match, so the guidance is strong but not fully comparative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

proxenio_set_api_keySet Proxenio API KeyA

Idempotent

Configure the API key for authenticating with Proxenio's agent API.

This must be called before using proxenio_get_matches or proxenio_accept_match.

The API key is generated by a verified human principal at https://www.proxenio.ai/agents. Keys are 36 characters, start with 'prx_', and inherit the principal's trust tier.

Args:

api_key (string): The full API key starting with 'prx_' (36 characters)

Returns: Confirmation that the key was set, or an error if the format is invalid.

Examples:

Use when: Setting up Proxenio access for the first time
Use when: Switching to a different principal's API key
Don't use when: Key is already configured and working

ParametersJSON Schema

Name	Required	Description	Default
`api_key`	Yes	Proxenio API key (36 chars, starts with 'prx_'). Generated by the human principal at https://www.proxenio.ai/agents

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds meaningful context: the key must be generated by a verified human principal, inherits trust tier, and returns confirmation or format error. It does not contradict annotations and enriches understanding of the operation's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Args, Returns, Examples) and is appropriately sized for a configuration tool. However, the Args section repeats schema information verbatim, which adds slight redundancy. Overall, it earns its place and is easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema), the description covers all necessary context: the prerequisite call, the key's provenance and format, the return value, and explicit usage scenarios. The annotations cover safety properties. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: the schema already fully describes the api_key parameter, including pattern, length, and generation URL. The description's Args section merely repeats what the schema states (e.g., 'starts with prx_', 36 characters) without adding new semantic detail, so it stays at the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb and resource: 'Configure the API key for authenticating with Proxenio's agent API.' It is immediately distinguishable from sibling tools like proxenio_get_matches or proxenio_accept_match, which operate on matches rather than configuration.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says this must be called before using proxenio_get_matches or proxenio_accept_match, and provides concrete 'Use when' and 'Don't use when' scenarios. This is outstanding guidance for when to invoke the tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

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TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a distinct, non-overlapping role: discover platform info, set authentication, retrieve matches, and accept a match. The separation is clear and descriptions reinforce the intended use.

Naming Consistency5/5

All tools follow a consistent 'proxenio_<verb>_<noun>' naming pattern (e.g., proxenio_get_matches, proxenio_accept_match). The convention is uniform and predictable.

Tool Count5/5

With only 4 tools, the server is tightly scoped and each tool earns its place. This is ideal for the platform's narrow purpose of discovering, authenticating, and processing matches.

Completeness4/5

The core lifecycle is covered: discover, authenticate, list matches, and accept. A 'reject' or 'decline' action is absent, but the primary use case of accepting appropriate introductions is fully supported.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

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Proxenio MCP Server

What It Does

Prerequisites

Installation

Usage with Claude Desktop

Usage with Cursor

Remote Deployment (HTTP)

Tools Reference

proxenio_discover

proxenio_set_api_key

proxenio_get_matches

proxenio_accept_match

Trust Model

Rate Limits

Security

Links

License

Available Tools

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

Latest Blog Posts

MCP directory API

`proxenio_discover`

`proxenio_set_api_key`

`proxenio_get_matches`

`proxenio_accept_match`