Universal Coder Bridge
An MCP+HTTP control plane for routing work to multiple coding-agent CLIs through a normalized contract, enabling multi-agent coding pipelines with planning, implementation, review, and revision.
README
Universal Coder Bridge
A production-oriented MCP + HTTP control plane for routing work to multiple coding-agent CLIs through one normalized contract.
ChatGPT / Codex / Claude / MCP client / private control UI
│
Streamable HTTP MCP :8787
│
Universal Coder Bridge
│
Hermes → OpenCode → Kilo → [optional AGY] → Hermes
plan implement review finish synthesize
│
/opt/data/workspace
The bridge keeps each CLI's native configured model by default. A caller can override a model for one run without rewriting the CLI's persistent configuration.
What is included
- Stateful MCP Streamable HTTP endpoint at
/mcp - Local MCP
stdiomode - Authenticated REST API and run-event SSE
- Normalized adapters for Hermes, OpenCode, Kilo Code, AGY, Codex CLI, Claude Code, and Gemini CLI
- Default pipeline: plan → implement → independent review → bounded revision → optional finish → final synthesis
- Per-agent and global concurrency limits
- Timeouts, cancellation, process-group termination, heartbeats, output tails, and durable artifacts
- Restart recovery for interrupted runs
- Workspace traversal and symlink-escape protection
- Host-header validation and secret redaction
- Docker, systemd, and Caddy deployment files
Telegram is deliberately not part of this build.
Adapter status
| Adapter | Default state | Role |
|---|---|---|
| Hermes | Enabled | Orchestrator, planner, final synthesis |
| OpenCode | Enabled | Implementation and repository editing |
| Kilo Code | Enabled | Review, debugging, security, risk checks |
| AGY | Disabled | Optional integration/automation finisher; enable only after confirming its local command syntax |
| Codex CLI | Disabled | Optional universal coder |
| Claude Code | Disabled | Optional universal coder |
| Gemini CLI | Disabled | Optional universal coder |
All commands are configured in config/agents.json; the bridge does not invoke an arbitrary shell.
MCP tools
| Tool | Purpose |
|---|---|
agent_describe |
List adapters, roles, capabilities, commands, and activity |
agent_health |
Check executable availability and versions |
agent_execute |
Queue one task on one coder |
pipeline_execute |
Run the universal multi-agent coding pipeline |
agent_continue |
Create a bridge-level follow-up run from a completed run |
agent_get_run |
Read status, PID, heartbeat, output tails, and pipeline steps |
agent_list_runs |
List recent runs |
agent_cancel |
Cancel queued/running work and terminate the active process group |
agent_list_artifacts |
List bridge-created files for a run |
agent_read_artifact |
Read one bounded UTF-8 artifact |
agent_continue grounds a new task in the previous run and current repository state. It does not promise native session resumption inside every third-party CLI.
HTTP endpoints
GET /health— unauthenticated liveness checkGET /api/agents— adapter configuration and live healthGET /api/runs?limit=25— recent runsPOST /api/runs— submit an agent or pipeline runGET /api/runs/:id— inspect one runPOST /api/runs/:id/continue— submit a follow-up runDELETE /api/runs/:id— cancel one runGET /api/runs/:id/events— Server-Sent Events streamPOST|GET|DELETE /mcp— MCP Streamable HTTP transport
Runtime defaults
Port: 8787
HTTP bind: 127.0.0.1
Workspace root: /opt/data/workspace
Artifact root: /opt/data/artifacts
Log file: /opt/data/logs/bridge.log
Global run slots: 2
Model behavior: native unless explicitly overridden
Install on Ubuntu VPS
Use Node.js 20 or newer.
sudo mkdir -p /opt/universal-coder-bridge
sudo chown "$USER":"$USER" /opt/universal-coder-bridge
cd /opt/universal-coder-bridge
# Copy or extract this project here.
npm install --no-audit --no-fund
npm run check
npm run verify:runtime
cp .env.example .env
cp config/agents.example.json config/agents.json
Generate a service token:
openssl rand -hex 32
Place it in .env as BRIDGE_AUTH_TOKEN. Keep the bridge on 127.0.0.1 when Caddy is the public HTTPS entry point.
Each enabled coder must be installed and authenticated for the same Linux user that runs the bridge:
hermes --version
opencode --version
kilo --version
Enable only the adapters whose command syntax you have verified locally.
Start directly:
npm run build
npm start
curl http://127.0.0.1:8787/health
Systemd deployment
Create a dedicated unprivileged user and runtime directories:
sudo useradd --system --create-home --shell /usr/sbin/nologin sorenbridge
sudo mkdir -p /opt/data/{workspace,artifacts,logs}
sudo chown -R sorenbridge:sorenbridge /opt/data
sudo chown -R sorenbridge:sorenbridge /opt/universal-coder-bridge
Install the environment and unit:
sudo cp .env.example /etc/universal-coder-bridge.env
sudo chmod 600 /etc/universal-coder-bridge.env
sudo cp deploy/systemd/universal-coder-bridge.service /etc/systemd/system/
sudo systemctl daemon-reload
sudo systemctl enable --now universal-coder-bridge
sudo systemctl status universal-coder-bridge
journalctl -u universal-coder-bridge -f
The service unit sets HOME=/home/sorenbridge because agent CLIs commonly keep authentication and writable caches under the service user's home. Install and authenticate each CLI as sorenbridge; do not run the bridge as root.
Caddy and allowed hosts
Copy deploy/caddy/Caddyfile.example, replace bridge.example.com, and keep streaming enabled.
The public hostname must also appear in ALLOWED_HOSTS:
ALLOWED_HOSTS=localhost,127.0.0.1,[::1],bridge.example.com
Remote MCP client
{
"mcpServers": {
"universal-coders": {
"url": "https://bridge.example.com/mcp",
"headers": {
"Authorization": "Bearer YOUR_BRIDGE_TOKEN"
}
}
}
}
A static bearer token is appropriate for a private, service-to-service bridge. Put a standards-compliant OAuth or identity-aware gateway in front before exposing it as a public multi-user service.
Run one coder
curl -X POST http://127.0.0.1:8787/api/runs \
-H "Authorization: Bearer $BRIDGE_AUTH_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"agentId": "opencode",
"task": "Inspect the project, run tests, and fix the failing test.",
"workspace": "my-project",
"model": {"mode": "native"}
}'
One-run model override:
{
"agentId": "opencode",
"task": "Implement the feature and verify it.",
"workspace": "my-project",
"model": {"mode": "override", "value": "provider/model"}
}
Run the universal pipeline
curl -X POST http://127.0.0.1:8787/api/runs \
-H "Authorization: Bearer $BRIDGE_AUTH_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"kind": "pipeline",
"task": "Add authenticated project sharing and verify it end to end.",
"workspace": "my-project",
"plannerId": "hermes",
"implementerId": "opencode",
"reviewerId": "kilo",
"finalizerId": "hermes",
"maxRevisions": 1
}'
To include a verified finisher adapter, add "finisherId": "agy" after enabling AGY.
Continue a completed run
curl -X POST http://127.0.0.1:8787/api/runs/RUN_ID/continue \
-H "Authorization: Bearer $BRIDGE_AUTH_TOKEN" \
-H "Content-Type: application/json" \
-d '{"instruction":"Run the full regression suite and fix anything related."}'
Add another coding CLI
Add an object to config/agents.json:
{
"id": "new-coder",
"displayName": "New Coder",
"description": "What it is responsible for.",
"role": "implementer",
"enabled": true,
"command": "new-coder",
"args": ["run", "{{prompt}}"],
"inputMode": "argument",
"modelArgs": ["--model", "{{model}}"],
"modelArgsIndex": 1,
"env": {},
"capabilities": ["implement", "test"],
"timeoutSeconds": 1200,
"maxConcurrency": 1,
"versionArgs": ["--version"]
}
Templates supported in args: {{prompt}}, {{workspace}}, and {{runId}}. {{model}} is supported in modelArgs.
modelArgsIndex is a zero-based insertion position in the base args array. Set it so model flags never split a flag from the value it consumes. Examples:
Hermes: [chat, --model, MODEL, -q, PROMPT] index 1
OpenCode: [run, --model, MODEL, PROMPT] index 1
Kilo: [run, --auto, --model, MODEL, PROMPT] index 2
Claude: [--model, MODEL, -p, PROMPT, ...] index 0
For CLIs that read the task from stdin, use "inputMode": "stdin"; the configured argument list remains shell-free.
Security boundaries
- Only configured executables and argument arrays are spawned; there is no arbitrary
root_shelltool. - Workspaces must remain under
WORKSPACE_ROOT, including after symlink resolution. - HTTP binding to a non-loopback address without
BRIDGE_AUTH_TOKENis rejected at startup. - Host headers are checked against
ALLOWED_HOSTS. - Authorization tokens are redacted from structured logs.
- Runs have bounded timeouts, cancellation, output capture limits, heartbeats, and process-group termination.
run.json,stdout.log, andstderr.logare persisted under the artifact root.- Runs left active by an unexpected restart are recovered as failed instead of remaining permanently “running.”
- Stdio mode writes bridge logs to stderr so MCP protocol messages on stdout remain clean.
The coding CLIs can still edit files and execute commands according to their own permissions. Keep .env, SSH keys, API keys, deployment credentials, and unrelated repositories outside WORKSPACE_ROOT. For hostile or untrusted workloads, add a stronger per-run container, VM, or sandbox boundary.
Docker
cp .env.example .env
docker compose up --build -d
Compose overrides the container bind address to 0.0.0.0, while publishing the host port only on 127.0.0.1:8787.
The base image contains the bridge, not the coding CLIs. Extend the image with only the adapters you need, or use systemd so the bridge can reach host-installed CLIs and their user-scoped credentials.
Local stdio mode
BRIDGE_TRANSPORT=stdio npm start
Development and verification
npm install --no-audit --no-fund
npm run typecheck
npm test
npm run verify:runtime
npm run build
See VERIFICATION.md for the checks completed when this package was generated and the remaining environment-dependent verification steps.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.