$ loading_
Bridge A2A remote agents into MCP tools for stateless task invocation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "a2a-mcp-bridge" yet — see the docs or source repo.
Project the available A2A remote agent skills as namespaced MCP tools, and list each tool name with its corresponding skill.
A list of namespaced MCP tools and the A2A skills each one maps to.
Invoke a target A2A agent skill through the MCP Tasks extension, execute it as a stateless task, and return the result.
A one-off task result from the remote agent skill without relying on long-lived session state.
Expose skills from multiple A2A agents as MCP tools under different namespaces to avoid naming conflicts.
A namespace layout grouped by agent or skill domain for easier client invocation and management.
Developers with existing A2A remote agents can project agent skills into MCP tools so MCP-capable clients can call them directly. This avoids building separate client integrations for each agent.
When a workflow is better suited to one-off tasks than persistent conversations, this tool enables stateless A2A agent invocation through the MCP Tasks extension. It fits task-oriented remote agent execution.
When multiple remote agents are involved, namespaces can organize their skills into a unified MCP tool surface. This makes it easier for clients to discover, distinguish, and invoke different agent capabilities.
It bridges Agent2Agent (A2A) remote agents to MCP clients and projects each agent skill as a namespaced MCP tool. It supports stateless, task-oriented invocation through the MCP Tasks extension.
The provided description says it supports a stateless, task-oriented invocation model through the MCP Tasks extension. For more specific invocation details, see the source repository.
No trustworthy documentation or installation instructions are provided here. For setup, configuration, and runtime prerequisites, see the source repository.
Connect MCP-capable agents to A2A endpoints for agent-to-agent messaging.
Aggregate local MCP servers into one endpoint with runtime control and hot reload.
Bridge A2A governance into MCP workflows for managed AI integration.
Turn HTTP operations and cURL commands into safe local-first MCP tools.
Expose reusable team skills to MCP agents via package.json configuration.
Lets AI securely query multi-vendor routers and assist network troubleshooting.