agent-bridge-mcp
Enables communication between local desktop agent (Amazon Quick) and cloud DevSpaces agent (Kiro) via an Amazon S3 message store, providing tools for sending, receiving, and managing messages, tasks, and conversations.
Click on "Deploy 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., "@agent-bridge-mcpCheck my inbox for new messages from Quick"
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.
Agent Bridge MCP Server
An MCP server + Lambda API that enables real-time communication between Kiro and Amazon Quick across environments (local Windows ↔ cloud DevSpaces). Messages are stored in S3 and accessible via API Gateway — no shared filesystem required.
Architecture
┌──────────────────┐ ┌──────────────────┐
│ Amazon Quick │ │ Kiro │
│ (Windows PC) │ │ (DevSpaces) │
│ │ │ │
│ MCP Server │ ┌──────────┐ │ curl / shell │
│ (stdio, boto3) │────────►│ S3 │◄───────│ │
│ │ │ bucket │ │ │
│ — OR — │ └──────────┘ │ — OR — │
│ │ ▲ │ │
│ Lambda invoke │ │ │ API Gateway │
│ (via Matilda) │────────►┌────┴─────┐◄───────│ (HTTPS POST) │
│ │ │ Lambda │ │ │
└──────────────────┘ └──────────┘ └──────────────────┘Related MCP server: claude-intercom
Components
Component | Purpose |
| Local MCP server (stdio) — Quick connects directly via S3 |
| Lambda function — HTTP API relay to same S3 store |
API Gateway | Public HTTPS endpoint for Kiro (DevSpaces can't hit Lambda URLs directly) |
S3 Bucket | Shared message store |
Endpoints
Who | How they connect |
Quick | MCP server (local stdio) with |
Kiro |
|
Setup
Prerequisites
Python 3.10+
pip install mcp boto3AWS credentials with S3 access
Environment Variable
export AGENT_BRIDGE_BUCKET=your-bucket-nameAmazon Quick (local MCP)
Settings → Capabilities → MCP → Add Server:
Command:
pyArgs: path to
server.pyEnv:
AGENT_BRIDGE_BUCKET=your-bucket-name
Kiro (DevSpaces — via API Gateway)
# Send a message
curl -s -X POST "https://<your-api-id>.execute-api.<region>.amazonaws.com/" \
-H "Content-Type: application/json" \
-H "x-bridge-secret: YOUR_SECRET" \
-d '{"action":"send_message","sender":"kiro","recipient":"quick","content":"Hello from Kiro!"}'
# Check for messages
curl -s -X POST "https://<your-api-id>.execute-api.<region>.amazonaws.com/" \
-H "Content-Type: application/json" \
-H "x-bridge-secret: YOUR_SECRET" \
-d '{"action":"get_messages","agent":"kiro"}'
# Get stats
curl -s -X POST "https://<your-api-id>.execute-api.<region>.amazonaws.com/" \
-H "Content-Type: application/json" \
-H "x-bridge-secret: YOUR_SECRET" \
-d '{"action":"get_stats"}'API Actions
All requests are POST with JSON body containing "action" plus parameters:
Action | Parameters | Description |
|
| Send a message |
|
| Check inbox |
|
| Mark messages read |
|
| List threads |
|
| Full thread history |
| (none) | Bridge statistics |
Message Types
message, task, response, context, status, question
S3 Structure
bridge/
├── inbox/
│ ├── quick/ ← Quick's messages
│ └── kiro/ ← Kiro's messages
└── conversations/
└── {conv_id}/
├── meta.json ← Thread metadata
└── messages/ ← Chronological messagesSecurity
S3 bucket: private, all public access blocked
API Gateway: secured by
x-bridge-secretheader checked in Lambda codeLambda function URL:
AuthType: NONE(backup path)
AWS Resources (you'll create these)
S3 Bucket: any name (set as
AGENT_BRIDGE_BUCKET)Lambda: handles API actions against the S3 bucket
API Gateway: HTTP API fronting the Lambda
IAM Role: Lambda execution role with S3 read/write on the bucket
License
MIT
This server cannot be deployed
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