Skip to main content
Glama

request_intro

Propose an introduction to a matched contact through mutual approval. Send a message explaining the value, requiring both parties to consent before connecting.

Instructions

Propose an introduction to someone you matched with. They'll see your message and can approve or decline. Nothing happens without both sides saying yes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
match_idYesMatch ID from search_matches
toYesAgent ID of the person you want to meet
messageYesShort message explaining why this intro would be valuable

Implementation Reference

  • Handler function that executes the request_intro tool logic. Makes POST request to /api/intros endpoint with match details, agent credentials, and cryptographic signature. Returns intro ID and pending status on success, or error message on failure.
    async (args) => {
      try {
        const result = await api("/api/intros", {
          method: "POST",
          body: JSON.stringify({
            matchId: args.match_id,
            targetAgentId: args.to,
            message: args.message,
            fieldsToDisclose: ["needs", "offers"],
            agentId,
            publicKey: keys.publicKey,
            signature: sign(args.match_id + args.message, keys.privateKey),
          }),
        });
    
        if (result.error) return { content: [{ type: "text" as const, text: `Failed: ${result.error}` }], isError: true };
    
        return {
          content: [{
            type: "text" as const,
            text: JSON.stringify({
              introId: result.introId,
              status: "pending",
              to: args.to,
              note: "Intro request sent. They'll see it in their digest.",
            }, null, 2),
          }],
        };
      } catch (e: any) {
        return { content: [{ type: "text" as const, text: `Network error: ${e.message}` }], isError: true };
      }
    }
  • Input schema defining three required string parameters: match_id (from search results), to (target agent ID), and message (explanation for the intro).
    {
      match_id: z.string().describe("Match ID from search_matches"),
      to: z.string().describe("Agent ID of the person you want to meet"),
      message: z.string().describe("Short message explaining why this intro would be valuable"),
    },
  • src/index.ts:199-239 (registration)
    Complete tool registration calling server.tool() with name 'request_intro', description, input schema, and handler function. Registers the tool with the MCP server.
    server.tool(
      "request_intro",
      "Propose an introduction to someone you matched with. They'll see your message and can approve or decline. Nothing happens without both sides saying yes.",
      {
        match_id: z.string().describe("Match ID from search_matches"),
        to: z.string().describe("Agent ID of the person you want to meet"),
        message: z.string().describe("Short message explaining why this intro would be valuable"),
      },
      async (args) => {
        try {
          const result = await api("/api/intros", {
            method: "POST",
            body: JSON.stringify({
              matchId: args.match_id,
              targetAgentId: args.to,
              message: args.message,
              fieldsToDisclose: ["needs", "offers"],
              agentId,
              publicKey: keys.publicKey,
              signature: sign(args.match_id + args.message, keys.privateKey),
            }),
          });
    
          if (result.error) return { content: [{ type: "text" as const, text: `Failed: ${result.error}` }], isError: true };
    
          return {
            content: [{
              type: "text" as const,
              text: JSON.stringify({
                introId: result.introId,
                status: "pending",
                to: args.to,
                note: "Intro request sent. They'll see it in their digest.",
              }, null, 2),
            }],
          };
        } catch (e: any) {
          return { content: [{ type: "text" as const, text: `Network error: ${e.message}` }], isError: true };
        }
      }
    );
  • Helper function that wraps fetch API calls with required headers including agent ID and public key for authentication. Used by the request_intro handler to communicate with the backend API.
    async function api(path: string, opts?: RequestInit): Promise<any> {
      const res = await fetch(`${API}${path}`, {
        ...opts,
        headers: {
          "Content-Type": "application/json",
          "X-Agent-Id": agentId,
          "X-Public-Key": keys.publicKey,
          ...opts?.headers,
        },
      });
      return res.json();
    }
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains the workflow ('They'll see your message and can approve or decline') and safety mechanism ('Nothing happens without both sides saying yes'), which are crucial behavioral traits not covered by the input schema. It doesn't mention rate limits or authentication needs, but covers the core interaction model well.

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

Conciseness5/5

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

The description is perfectly concise with two sentences that each earn their place. The first sentence states the purpose, the second explains the workflow and safety mechanism. There's zero wasted language and it's front-loaded with the core action.

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

Completeness4/5

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

Given the tool's moderate complexity (3 required parameters, no output schema, no annotations), the description provides good contextual completeness. It explains the purpose, workflow, and safety mechanism. The main gap is lack of information about return values or what happens after approval/decline, but this is reasonable given the tool's scope.

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%, so the schema already documents all three parameters thoroughly. The description doesn't add any additional meaning about the parameters beyond what's in the schema descriptions. This meets the baseline of 3 when the schema does the heavy lifting.

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 specific action ('Propose an introduction'), identifies the resource ('someone you matched with'), and explains the outcome ('They'll see your message and can approve or decline'). It distinguishes this from sibling tools like 'respond_to_intro' by focusing on initiating rather than responding to introductions.

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 clear context for when to use this tool ('to someone you matched with') and mentions the prerequisite ('Match ID from search_matches'). However, it doesn't explicitly state when not to use it or name alternatives among sibling tools like 'respond_to_intro' or 'search_matches' for different scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/aeoess/mingle-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server