Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@A2A MCP Serverlist available agents"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A2A MCP Server
An MCP server that implements an A2A Client for the A2A Protocol. The server can be used to connect and send messages to A2A Servers (remote agents).
The server needs to be initialised with one or more Agent Card URLs, each of which can have custom headers for authentication, configuration, etc.
All agents (name and description) can be viewed with the get_agents() tool, an agent's skills (name and description) can be viewed with the get_agent tool, messages can be sent to the agents with the send_message tool, and Artifacts can be viewed with view_text_artifact and view_data_artifact tools.
✨ Features
Connect to any A2A Agent
Use custom headers for authentication and configuration
View Agent Cards and Skills
Send messages to agents
Continue conversations with agents
View Artifacts that would overload the context
Tasks are stored in JSON format in
~/.a2a-mcp/tasks/File bytes and URLs are converted and downloaded to
~/.a2a-mcp/files/
📋 Requirements
To run the server you need to install uv if you haven't already.
MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | shWindows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"🚀 Quick Start
Download Claude for Desktop
Add the below to your Claude Desktop config (
~/Library/Application Support/Claude/claude_desktop_config.jsonon macOS):
{
"mcpServers": {
"a2a": {
"command": "uvx",
"args": ["a2anet-mcp"],
"env": {
"A2A_MCP_AGENT_CARDS": "{\"tweet-search\": {\"url\": \"https://example.com/.well-known/agent-card.json\"}}"
}
}
}
}Tip: If you don't have an Agent Card URL, see: A2A Net Demo
⚙️ Configuration
All configuration is via environment variables prefixed with A2A_MCP_.
A2A_MCP_AGENT_CARDS (required)
A JSON object mapping agent IDs to their configuration. Each agent must have a url key with the full path to the Agent Card. It can optionally have a custom_headers key with an object in the form {"header": "value"}:
export A2A_MCP_AGENT_CARDS='{
"tweet-search": {
"url": "https://example.com/.well-known/agent-card.json",
"custom_headers": {"X-API-Key": "your-key"}
}
}'Optional settings
Env Var | Default | Description |
|
| Enable task persistence via |
|
| Enable file artifact storage via |
|
| Character limit for artifact minimization in |
|
| Max string length when minimizing objects |
|
| Character limit for |
🛠️ Tools
get_agents
Get all agent names and descriptions.
get_agent
Get an agent's name, description, and skill names and descriptions.
Parameter | Required | Description |
| Yes | Agent ID |
send_message
Send a message to an agent.
Parameter | Required | Description |
| Yes | Agent ID from |
| Yes | Your message or request |
| No | Continue an existing conversation |
| No | Task ID for input_required flows |
view_text_artifact
View text content from an artifact with optional line or character range selection.
Parameter | Required | Description |
| Yes | Agent ID that produced the artifact |
| Yes | Task ID containing the artifact |
| Yes | Artifact to view |
| No | Starting line number (1-based, inclusive) |
| No | Ending line number (1-based, inclusive) |
| No | Starting character index (0-based) |
| No | Ending character index (0-based) |
view_data_artifact
View structured data from an artifact with optional filtering.
Parameter | Required | Description |
| Yes | Agent ID that produced the artifact |
| Yes | Task ID containing the artifact |
| Yes | Artifact to view |
| No | Dot-separated path to extract specific fields |
| No | Row selection (index, list, range string, or "all") |
| No | Column selection (name, list, or "all") |
📖 Examples
List agents
get_agents({}){
"tweet-search": {
"name": "Tweet Search",
"description": "Find and analyze tweets by keyword, URL, author, list, or thread. Filter by language, media type, engagement, date range, or location. Get a clean table of tweets with authors, links, media, and counts; then refine the table and generate new columns with AI."
}
}Get agent details
get_agent({
"agent_id": "tweet-search"
}){
"name": "Tweet Search",
"description": "Find and analyze tweets by keyword, URL, author, list, or thread. Filter by language, media type, engagement, date range, or location. Get a clean table of tweets with authors, links, media, and counts; then refine the table and generate new columns with AI.",
"skills": [
{
"name": "Search Tweets",
"description": "Search X by keywords, URLs, handles, or conversation IDs. Filter by engagement (retweets/favorites/replies), dates, language, location, media type (images/videos/quotes), user verification status, and author/reply/mention relationships. Sort by Top or Latest. Return 1-10,000 results."
},
{
"name": "View Table",
"description": "View specific rows and columns from any table, ask questions about it, and analyse it with AI. If the agent performs searches, explain which rows are good and bad to improve the search."
},
{
"name": "Filter Table",
"description": "Filter any table with traditional filtering (i.e. patterns like names, URLs, etc). Explain what table you want to filter, and what rows you want to keep or remove."
},
{
"name": "Filter Table with AI",
"description": "Filter any table with AI filtering (i.e. reasoning, semantic understanding, etc). Explain what table you want to filter, and what rows you want to keep or remove."
},
{
"name": "Generate Table",
"description": "Generate a new table from any table with AI. Explain what table you want to generate from, what columns you want to keep, and what new columns you want to generate."
}
]
}Send a message
send_message({
"agent_id": "tweet-search",
"message": "Find tweets about AI from today (January 12, 2026)"
}){
"id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"context_id": "cc9b9234-ecb7-4938-901a-a79912b8239f",
"kind": "task",
"status": {
"state": "completed",
"message": {
"context_id": "cc9b9234-ecb7-4938-901a-a79912b8239f",
"kind": "message",
"parts": [
{
"kind": "text",
"text": "I found 10 tweets about \"AI\" posted on January 12, 2026. The search parameters used were:\n\n- Search Terms: AI\n- Start Date: 2026-01-12\n- End Date: 2026-01-13\n- Maximum Items: 10\n\nWould you like to see more tweets, or do you want a summary or analysis of these results?"
}
]
}
},
"artifacts": [
{
"artifact_id": "97157147-db9f-490c-bc56-5603c99fd23b",
"description": "Tweets about AI posted on January 12, 2026.",
"name": "AI Tweets from January 12, 2026",
"parts": [
{
"kind": "data",
"data": {
"records": {
"_total_rows": 10,
"_columns": [
{
"count": 1,
"unique_count": 1,
"types": [
{
"name": "int",
"count": 1,
"percentage": 100.0,
"sample_value": 213,
"minimum": 213,
"maximum": 213,
"average": 213
}
],
"name": "quote.author.mediaCount"
},
...,
{
"count": 10,
"unique_count": 1,
"types": [
{
"name": "bool",
"count": 10,
"percentage": 100.0,
"sample_value": false
}
],
"name": "isPinned"
}
]
},
"_tip": "Data was minimized. Call view_data_artifact() to navigate to specific data."
}
}
]
}
]
}Multi-turn conversation
Use context_id to continue a conversation:
send_message({
"agent_id": "tweet-search",
"message": "Can you summarize each of the 10 tweets in the table in 3-5 words each? Just give me a simple list with the author name and summary.",
"context_id": "cc9b9234-ecb7-4938-901a-a79912b8239f"
}){
"id": "f8e7d6c5-b4a3-2109-fedc-ba9876543210",
"context_id": "cc9b9234-ecb7-4938-901a-a79912b8239f",
"kind": "task",
"status": {
"state": "completed",
"message": {
"context_id": "cc9b9234-ecb7-4938-901a-a79912b8239f",
"kind": "message",
"parts": [
{
"kind": "text",
"text": "Here is a simple list of each tweet's author and a 3-5 word summary:\n\n1. alienofeth – Real-time STT intent detection\n2. UnderdogEth_ – AI ownership discussion thread\n3. Count_Down_000 – Learning new vocabulary word\n4. ThaJonseBoy – AI and market predictions\n5. Evelyn852422353 – AI model comparison debate\n6. SyrilTchouta – Language learning with AI\n7. cx. – AI in marketing insights\n8. Halosznn_ – Graphic design course shared\n9. xmaquina – AI smarter models discussion\n10. Flagm8_ – AI and business strategy\n\nLet me know if you want more details or a different format!"
}
]
}
},
"artifacts": [
{
"artifact_id": "ed350a03-c6ef-4154-9163-6c56418ee7a7",
"description": "A simple list of each tweet's author and a 3-5 word summary of the tweet content.",
"name": "AI Tweet Summaries 3-5 Words",
"parts": [
{
"kind": "data",
"data": {
"records": [
{
"author.userName": "ai_q2_",
"summary": "Possibly understand"
},
{
"author.userName": "UnderdogEth_",
"summary": "AI evolving into reliable teammate"
},
{
"author.userName": "Heisrollo",
"summary": "AI takeover in industry"
},
{
"author.userName": "_Fabichou_",
"summary": "Learned new word 'Unendlich'"
},
{
"author.userName": "alienofeth",
"summary": "AI ownership over smarter models"
},
{
"author.userName": "painted_by_ai",
"summary": "New Year greetings with superheroes"
},
{
"author.userName": "Pereira_Guto2",
"summary": "Norman absent due illness"
},
{
"author.userName": "HamzatMusaOpey1",
"summary": "WEEX AI Trading Hackathon"
},
{
"author.userName": "Count_Down_000",
"summary": "Self-taught AI philosophy learner"
},
{
"author.userName": "CallStackTech",
"summary": "Real-time STT intent detection"
}
]
}
}
]
}
]
}View data artifact
view_data_artifact({
"agent_id": "tweet-search",
"task_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"artifact_id": "97157147-db9f-490c-bc56-5603c99fd23b",
"json_path": "records",
"rows": "all",
"columns": ["author.userName", "text"]
}){
"artifact_id": "97157147-db9f-490c-bc56-5603c99fd23b",
"description": "Tweets about AI posted on January 12, 2026.",
"name": "AI Tweets from January 12, 2026",
"parts": [
{
"kind": "data",
"data": [
{
"author.userName": "ai_q2_",
"text": "@nyank_x わかるかもしれない"
},
{
"author.userName": "UnderdogEth_",
"text": "@ThaJonseBoy @HeyElsaAI @HeyElsaAI is turning AI from a tool you use into a teammate you actually rely on."
},
{
"author.userName": "Heisrollo",
"text": "As you're learning this, you should understand it's one of the industries AI is about to completely takeover."
},
{
"author.userName": "_Fabichou_",
"text": "@SyrilTchouta Unendlich😌 j'ai appris un nouveau mot"
},
{
"author.userName": "alienofeth",
"text": "@Evelyn852422353 @xmaquina @xmaquina is about AI ownership, not just smarter models."
},
{
"author.userName": "painted_by_ai",
"text": "#ClarkKent #BruceWayne #superbat\n新年明けましておめでとうございます(遅い) https://t.co/ShvzHBUvPJ"
},
{
"author.userName": "Pereira_Guto2",
"text": "@Amzng_Peter Acho tão engraçado que no primeiro filme não temos o Norman pq ele tava morrendo dessa doença e não tínhamos esse contexto, mas aí tínhamos o capanga genérico n1 falando pro Connors terminar o soro do lagarto"
},
{
"author.userName": "HamzatMusaOpey1",
"text": "@WEEX_Official 📢 WEEX AI Trading Hackathon is Here Again!!! 🔊🔊🔊\n\n@WEEX_Official AI trading /WEEX AI Hackathon is the best AI Trading I've ever used. It's accurate, reliable, and bug free."
},
{
"author.userName": "Count_Down_000",
"text": "@grok In other words, I am simply a self-taught person who is using the skills I gained from taking Japanese entrance exams, especially the Japanese and English reading comprehension questions, to learn about the philosophy and knowledge system behind the AI GROK and Gemini. https://t.co/IVf2mjGGX6"
},
{
"author.userName": "CallStackTech",
"text": "Just built a real-time STT pipeline that detects intent faster than you can say \"Hello!\" 🎤✨ Discover how I used Deepgram to achieve su...\n\n🔗 https://t.co/dgbvdlATZ0\n\n#VoiceAI #AI #BuildInPublic"
}
]
}
]
}💾 Data Storage
Tasks and file artifacts are persisted locally at ~/.a2a-mcp/:
Tasks:
~/.a2a-mcp/tasks/Files:
~/.a2a-mcp/files/
Both can be disabled via environment variables (A2A_MCP_TASK_STORE=false, A2A_MCP_FILE_STORE=false).
🔧 Development
Claude Desktop Setup
For local development:
Clone the repository:
git clone https://github.com/a2anet/a2a-mcp.gitDownload Claude for Desktop.
Add to the below to your Claude Desktop config (
~/Library/Application Support/Claude/claude_desktop_config.jsonon macOS):
{
"mcpServers": {
"a2a": {
"command": "uv",
"args": ["--directory", "/path/to/a2a-mcp", "run", "a2anet-mcp"],
"env": {
"A2A_MCP_AGENT_CARDS": "{\"tweet-search\": {\"url\": \"https://example.com/.well-known/agent-card.json\"}}"
}
}
}
}📄 License
a2anet is distributed under the terms of the Apache-2.0 license.
🤝 Join the A2A Net Community
A2A Net is a site to find and share AI agents and open-source community. Join to share your A2A agents, ask questions, stay up-to-date with the latest A2A news, be the first to hear about open-source releases, tutorials, and more!
🌍 Site: A2A Net
🤖 Discord: Join the Discord
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