Static source inference · medium confidence · detected: Logging
Deprecated protocol patterns detected
Summary
This server defines 8 tools with basic schemas and descriptions, but has significant quality gaps. Tool names follow verb_noun convention (register_agent, list_agents, send_task, etc.), which is good. However, descriptions are inconsistent in depth, some are one-liners (e.g., 'List all registered A2A agents') while others lack critical operational details. Input schemas are present but incomplete: many parameters lack descriptions, type constraints are missing, and required vs. optional fields are not always clear. The 'send_task' and 'subscribe_task' tools accept a generic 'message' object without documenting its structure, forcing LLMs to guess at valid payloads. Error handling is minimal, no guidance on recovery, retryability, or actionable next steps. Output schemas are not documented anywhere in the provided code, making it impossible for LLMs to understand what fields to expect from responses. The server uses STDIO transport only, which limits remote accessibility and production readiness. Overall, this reads like an early-stage bridge implementation that prioritizes functionality over LLM-centric tool design.
Tools (8)
cancel_taskwritesource verified60/100
Cancel a task
get_push_notificationread only50/100
Get the push notification configuration for a task
get_taskread onlysource verified62/100
Retrieve the status and results of a task
list_agentsread onlysource verified42/100
List all registered A2A agents
register_agentwritesource verified55/100
Register a new A2A agent with the MCP bridge server
send_taskwritesource verified52/100
Send a task to a registered A2A agent
set_push_notificationwrite50/100
Set push notification configuration for a task
subscribe_taskread only50/100
Subscribe to streaming updates from a task sent to an A2A agent
Generic 'message' object parameter lacks documentation of its internal structure. 'send_task' and 'subscribe_task' both accept a 'message' field of type 'object' with description 'Task message to send', but no guidance on what keys/fields it must contain. LLMs cannot construct valid payloads without this structure.
Output schemas completely undocumented. The code snippet shows tool definitions but does NOT show return type schemas. Tools like 'list_agents', 'get_task', and 'send_task' have no documented return structure, LLMs cannot plan downstream calls or extract required IDs for chaining.
Tool descriptions are too brief and lack operational context. 'List all registered A2A agents' (30 chars) tells LLMs WHAT but not WHY they should call it or WHEN. Missing: dependencies, prerequisites, what structure is revealed. Descriptions should be 50-200 chars with clear intent.
Recommendations
Document the internal structure of the 'message' parameter. Create an explicit schema or detailed description showing required fields, types, and examples. E.g.: 'message must be an object with keys: {"task": string, "args": object, "context": object (optional)}'. Publish this as a type definition or enum of valid message structures.
Add return type schemas to every tool. E.g., 'list_agents returns {agents: [{url: string, name: string, description: string, capabilities: object}], total: number}'. Include all fields agents need for downstream chaining (e.g., if get_task returns a task_id, confirm it's present so cancel_task can use it immediately).
Expand tool descriptions to 60-150 characters with explicit intent. E.g., 'list_agents → Retrieve all registered A2A agents and their capabilities. Call this first to discover available agents before sending tasks. Returns URL, name, description, and feature list.' This guides LLM selection.
Add detailed parameter descriptions with constraints. E.g., for 'metadata' in send_task: 'Optional dict of agent-specific metadata. Common keys: {"priority": "low|medium|high", "timeout_seconds": 60-3600, "retry_count": 0-5}. Agent ignores unknown keys.'
Document error conditions and recovery paths for each tool. E.g., 'send_task may fail with agent_not_found if agent_url is invalid. If so, call list_agents() to verify the URL, or register_agent() to add a new agent. Failures with task_failed indicate the agent rejected the message, review the error details and retry with a corrected message.'
Parameter descriptions are missing or generic. The 'metadata' field in 'send_task' is described as 'Optional metadata for the task', vague and non-actionable. What keys does it accept? Is it agent-specific? LLMs cannot use vague descriptions.
No error handling or recovery guidance. Code shows error responses with JSONRPC error codes (-32602), but tool definitions provide no guidance on what errors to expect or how to recover. E.g., 'send_task' may fail if agent_url is invalid, but no error message tells the LLM to 'try list_agents() first'.
Missing required vs. optional field clarity in schemas. 'send_task' input shows 'agent_url', 'message', 'sessionId', and 'metadata', but no JSON Schema 'required' array indicates which are mandatory. The code comment says agent_url must be in metadata, but the schema shows agent_url as a top-level param, inconsistent.
No pagination or result limits documented. 'list_agents' presumably returns all agents, but no mention of limits, pagination, or total count. If an agent registers thousands of agents, this could blow the context window.
Tool names do not always distinguish similar operations clearly. 'subscribe_task' vs 'get_task', the difference (streaming vs. point-in-time retrieval) is not obvious from names alone. Descriptions should clarify this, but current descriptions are too brief.
No idempotency or confirmation for destructive operations. 'cancel_task' is a WRITE operation with permanent consequences (task is cancelled), but no tool description warns of this or suggests a confirm step. Agents could accidentally cancel important tasks.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). Modern MCP spec supports tool annotations to flag destructive or read-only operations. This server does not use them, forcing LLMs to infer safety from descriptions alone.
cancel_taskset_push_notificationregister_agent
Add 'required' arrays to input schemas and clarify mutual exclusivity. E.g., if agent_url can come from either a top-level param or from metadata, document: 'Either agent_url param OR metadata.agent_url. If both provided, agent_url param takes precedence.'
Implement pagination for list_agents: add optional 'limit' (default 20, max 100) and 'offset' or 'cursor' params. Return total count and next_cursor in response so LLMs can fetch additional agents without hitting resource limits.
Rename or clarify get_task vs. subscribe_task. Consider: get_task (poll-based, point-in-time snapshot) vs. stream_task_updates (streaming, long-lived). Descriptions must explicitly state the difference: 'get_task returns the current state once; subscribe_task opens a streaming connection and returns updates as they arrive.'
Add destructiveHint annotation to cancel_task and set_push_notification (if it overwrites existing config). Annotate register_agent and cancel_task as WRITE operations. Annotate list_agents, get_task, get_push_notification as READ_ONLY. This helps LLMs reason about side effects.
Create a dry-run or confirmation workflow for cancel_task. E.g., add an optional 'dry_run' param: if true, return what would be cancelled without actually cancelling. Or require explicit confirmation: 'cancel_task requires confirmation: call confirm_cancel(task_id, confirmation_token) after receiving the token.'
Document the A2A protocol integration contract. What A2A message formats are supported? What agent capabilities are exposed? What happens if an agent fails or times out? This context should appear in tool descriptions or a server-level README reference.
Add explicit timeout and retry guidance. E.g., 'send_task may timeout if the agent is unresponsive. If timeout occurs, wait 5 seconds and retry once. If it fails again, check agent status via list_agents() or register_agent() to confirm the agent is available.'
Return fields that enable chaining. E.g., if send_task returns a task_id, list_agents should also return agent_id or agent_url so subsequent calls to get_task(task_id) can be enriched with context about which agent handled it. Include 'agent_url' in get_task response.
Add type constraints to parameter descriptions. E.g., 'task_id must be a UUID v4 string (36 characters, format: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx).' This prevents LLMs from passing malformed IDs.