Yes, A2a Bridge is free to use.

How do I install A2a Bridge?

A2a Bridge is a local plugin. Install it using npm package: a2a-bridge-mcp and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

Is A2a Bridge safe to use?

A2a Bridge was flagged by MCP Marketplace's security scan, scoring 4.2/10 (high risk). It has 3 high or critical findings to review. Review the security report on this page carefully before installing it.

What AI apps work with A2a Bridge?

A2a Bridge uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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A2a Bridge MCP Server

by Mdfifty50 Boop

Developer ToolsUse Caution4.2MCP RegistryLocal

Free

Server data from the Official MCP Registry

Agent-to-agent communication bridge for multi-agent systems

About

Agent-to-agent communication bridge for multi-agent systems

Security Report

4.2

Use Caution4.2High Risk

This MCP server implements agent-to-agent communication with capability discovery and task delegation. The code uses proper input validation with Zod schemas and follows MCP protocol standards. However, there are notable concerns around unvalidated agent identity acceptance, insufficient authorization checks for inter-agent operations, and a lack of authentication mechanisms for registering agents or delegating tasks. These gaps mean malicious agents could register with spoofed identities or intercept task results without proper authorization checks. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.

4 files analyzed · 13 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-mdfifty50-boop-a2a-bridge": {
      "args": [
        "-y",
        "a2a-bridge-mcp"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

a2a-bridge-mcp

MCP server for agent-to-agent communication -- capability discovery, task delegation, and result aggregation across MCP agents.

MCP connects agents to tools, but not to each other. This server adds a standardized agent-to-agent layer within the MCP protocol -- register agents, discover capabilities, delegate tasks, and broadcast work to multiple agents. Inspired by Google's A2A protocol.

Install

npx a2a-bridge-mcp

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "a2a-bridge": {
      "command": "npx",
      "args": ["a2a-bridge-mcp"]
    }
  }
}

From source

git clone https://github.com/mdfifty50-boop/a2a-bridge-mcp.git
cd a2a-bridge-mcp
npm install
node src/index.js

Tools

register_agent

Param	Type	Default	Description
`agent_id`	string	required	Unique agent identifier
`capabilities`	string[]	required	Capability strings (e.g. `["code-review", "summarization"]`)
`description`	string	`""`	Human-readable description
`input_schema`	object	`{}`	JSON schema for accepted input
`output_schema`	object	`{}`	JSON schema for produced output
`endpoint`	string	`""`	Optional endpoint or transport hint

discover_agents

Find agents matching a capability need with fuzzy text similarity scoring.

Param	Type	Default	Description
`capability_needed`	string	required	Capability to search for
`min_score`	number	0.3	Minimum similarity score (0-1)

Returns scored matches sorted by relevance.

delegate_task

Delegate a task to a specific registered agent. Creates a tracked task with status lifecycle.

Param	Type	Default	Description
`from_agent`	string	required	Delegating agent ID
`to_agent`	string	required	Target agent ID
`task_description`	string	required	What the target should do
`input_data`	object	`{}`	Input data for the task
`timeout_ms`	number	30000	Timeout in milliseconds

Returns a task_id for tracking.

get_task_result

Get status and result of a delegated task. Also used by executing agents to submit results.

Param	Type	Description
`task_id`	string	Task ID from delegate_task or broadcast_task
`submit_result`	object	(Optional) Submit completion result
`submit_error`	string	(Optional) Submit failure error

Status lifecycle: pending -> running -> completed / failed.

broadcast_task

Send a task to ALL agents matching a capability. Creates individual tracked tasks for each match.

Param	Type	Default	Description
`from_agent`	string	required	Broadcasting agent ID
`capability_needed`	string	required	Capability to match
`task_description`	string	required	What matched agents should do
`input_data`	object	`{}`	Input data
`min_score`	number	0.3	Minimum match score
`timeout_ms`	number	30000	Timeout per agent

Returns list of task IDs for aggregation via get_task_result.

get_agent_card

Get an agent's full capability card with schemas, stats, and task history.

Param	Type	Description
`agent_id`	string	Agent identifier

Returns capabilities, input/output schemas, success rate, and task counts. Inspired by Google A2A agent cards.

list_agents

List all registered agents, optionally filtered by capability.

Param	Type	Default	Description
`filter`	string	`""`	Capability keyword to filter by (empty = all)

Resources

URI	Description
`a2a://agents`	All registered agents with capabilities and stats

Usage Pattern

1. register_agent    -- each agent registers at startup
2. discover_agents   -- find who can handle a task
3. delegate_task     -- send work to a specific agent
   OR broadcast_task -- send work to all matching agents
4. get_task_result   -- poll for completion or submit results
5. get_agent_card    -- inspect an agent's full profile
6. list_agents       -- overview of the agent network

Multi-agent workflow example

Agent A (orchestrator):
  1. register_agent(agent_id="orchestrator", capabilities=["planning", "coordination"])
  2. discover_agents(capability_needed="code review")
     -> finds Agent B (score: 0.95)
  3. delegate_task(from="orchestrator", to="agent-b", task="Review PR #42")
     -> task_id: "task_1234"
  4. get_task_result(task_id="task_1234")
     -> status: "completed", result: { approved: true, comments: [...] }

Agent B (worker):
  1. register_agent(agent_id="agent-b", capabilities=["code-review", "linting"])
  2. (receives task via external notification or polling)
  3. get_task_result(task_id="task_1234", submit_result={ approved: true })

License

MIT

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A2a Bridge MCP Server

About

Security Report

Findings (13)Action required

Permissions Required

How to Install

Documentation

a2a-bridge-mcp

Install

Claude Desktop

From source

Tools

register_agent

discover_agents

delegate_task

get_task_result

broadcast_task

get_agent_card

list_agents

Resources

Usage Pattern

Multi-agent workflow example

License

Reviews

No reviews yet

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Git

Fetch

Toleno

mcp-creator-python

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