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GongRzhe

ACP-MCP-Server

by GongRzhe
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

convert_acp_message

Convert ACP message JSON to MCP-compatible format for integration between ACP agents and MCP clients, enabling communication and compatibility across protocols.

Instructions

Convert ACP message format to MCP-compatible format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
acp_message_jsonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • acp_mcp_server/message_bridge.py:120-132 (handler)
    The core handler function for the 'convert_acp_message' tool. It parses input JSON as ACPMessage, converts it to MCP format using MessageBridge.acp_to_mcp, and returns JSON-serialized MCP content.
    async def convert_acp_message(acp_message_json: str) -> str:
    """Convert ACP message format to MCP-compatible format"""
    try:
        import json
        message_data = json.loads(acp_message_json)
        acp_message = ACPMessage(**message_data)
        
        mcp_content = await bridge.acp_to_mcp([acp_message])
        
        return json.dumps([content.dict() for content in mcp_content], indent=2)
        
    except Exception as e:
        return f"Error: {e}"
  • acp_mcp_server/server.py:86-86 (registration)
    Invocation of register_bridge_tools which defines and registers the convert_acp_message tool using @mcp.tool() decorator.
    register_bridge_tools(self.mcp, self.message_bridge)

Tool Definition Quality

B3.1/5.0
Behavior2/5

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 states the conversion action but doesn't describe what the conversion entails (e.g., format changes, data loss, validation), whether it's idempotent, or what happens on errors. This leaves significant gaps for a transformation tool.

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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward conversion tool.

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

Completeness3/5

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

Given the tool's moderate complexity (format conversion), no annotations, and an output schema present, the description is minimally adequate. It states what the tool does but lacks details on behavior, parameters, or usage context. The output schema mitigates some gaps, but more guidance would be helpful.

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 schema has 0% description coverage, with one parameter 'acp_message_json' documented only by name and type. The description doesn't add any parameter-specific details (e.g., expected JSON structure, validation rules). However, with only one parameter, the baseline is 4, but the lack of compensation for the coverage gap reduces it to 3.

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 as converting ACP message format to MCP-compatible format, using specific verbs ('convert') and resources ('ACP message format', 'MCP-compatible format'). It doesn't explicitly distinguish from sibling tools like 'analyze_message_content' or 'smart_route_request', but the conversion focus is clear.

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 prerequisites (e.g., needing an ACP message), exclusions, or how it differs from sibling tools like 'analyze_message_content' that might handle message processing differently.

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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