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tesla0225

A2A Client MCP Server

by tesla0225

a2a_agent_info

Retrieve details about connected A2A agents, including their status and capabilities, to monitor and manage agent interactions within the protocol.

Instructions

Get information about the connected A2A agents

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentIdNoOptional agent ID. If not provided, information for all agents will be returned

Implementation Reference

  • index.ts:117-129 (registration)
    Registration of the 'a2a_agent_info' tool in the ListTools response, including name, description, and input schema.
    {
      name: "a2a_agent_info",
      description: "Get information about the connected A2A agents",
      inputSchema: {
        type: "object",
        properties: {
          agentId: {
            type: "string",
            description: "Optional agent ID. If not provided, information for all agents will be returned",
          },
        },
      },
    },
  • The handler logic for the 'a2a_agent_info' tool within the CallToolRequestSchema switch statement. It fetches and returns agent card information for a specific agent or all connected agents via agentManager clients.
    case "a2a_agent_info": {
      const { agentId } = args as { agentId?: string };
      
      if (agentId) {
        const client = agentManager.getClientById(agentId);
        if (!client) {
          throw new Error(`No agent found with ID ${agentId}`);
        }
        const card = await client.agentCard();
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(card, null, 2),
            },
          ],
        };
      } else {
        const results = [];
        for (const [id, client] of agentManager.getAllClients()) {
          try {
            const card = await client.agentCard();
            results.push({ agentId: id, card });
          } catch (error) {
            results.push({ agentId: id, error: error instanceof Error ? error.message : String(error) });
          }
        }
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(results, null, 2),
            },
          ],
        };
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information but lacks details on permissions, rate limits, response format, or whether it's a read-only operation. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned, how agents are defined, or any behavioral traits like error handling. For a tool with no structured data support, this leaves too many gaps for effective agent use.

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?

The input schema has 100% description coverage, clearly documenting the optional 'agentId' parameter. The description doesn't add any parameter semantics beyond what the schema provides, such as examples or constraints, so it meets the baseline score of 3 where the schema does the heavy lifting.

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

Purpose4/5

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 ('Get') and resource ('information about the connected A2A agents'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate itself from sibling tools like 'a2a_get_task', which might also retrieve information but about tasks rather than agents.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this tool is preferred, such as for agent-specific queries versus task-related ones, leaving the agent to infer usage from tool names alone.

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

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