Panel

Panel is a standalone remote MCP server that lets Claude call ChatGPT, DeepSeek, Kimi, and Gemini inside one persistent, shared discussion. It exposes exactly one tool:

ask_model(provider, message, conversation_id?)

Architecture

Streamable HTTP MCP endpoint: POST /mcp
Health endpoint: GET /health
Static bearer authentication on every MCP request
PostgreSQL source-of-truth transcript with one ordered log per conversation_id
One OpenAI-compatible adapter configured three ways, plus a native Gemini adapter
Request-time context compaction only; stored turns are never edited or deleted

The selected provider sees its own earlier turns as assistant/model. Claude and every other provider are rendered as user with [Speaker]: prefixes.

Local setup

Requirements: Node.js 22+, a reachable PostgreSQL database, and API keys for the four providers.

Copy .env.example to .env and fill values locally. Never commit .env.
Run npm ci.
Run npm run db:migrate (the server also initializes the idempotent schema at startup).
Run npm run dev.
In another terminal, run npm run manual.

Useful checks:

npm run build
npm run lint
npm test
npm run test:integration
npm run verify:persistence

The integration and persistence commands require DATABASE_URL. The manual test requires the running server, all provider keys, and PANEL_BEARER_TOKEN. Set PANEL_URL when testing a deployed instance.

Environment

Required server variables:

DATABASE_URL
PANEL_BEARER_TOKEN (use at least 32 random bytes)
OPENAI_API_KEY
DEEPSEEK_API_KEY
MOONSHOT_API_KEY
GOOGLE_API_KEY

Optional variables and defaults:

MAX_CONTEXT_CHARS=60000
PORT=3000
OPENAI_BASE_URL=https://api.openai.com/v1
OPENAI_MODEL=gpt-4o-mini
DEEPSEEK_BASE_URL=https://api.deepseek.com
DEEPSEEK_MODEL=deepseek-v4-flash
MOONSHOT_BASE_URL=https://api.moonshot.ai/v1
MOONSHOT_MODEL=kimi-k2.5
GEMINI_MODEL=gemini-2.5-flash

Deploy

Render

Push this repository to GitHub, create a Blueprint from render.yaml, and enter every sync: false secret in Render's dashboard. Point DATABASE_URL at external Neon or Supabase Postgres. The service URL will be https://<service>.onrender.com/mcp.

Railway

Push to GitHub, create a Railway project from the repository, and add the same variables. railway.json uses the included Dockerfile. Generate a public HTTPS domain and append /mcp.

Connect to claude.ai

Current Claude connector documentation lists fixed request-header authentication (static_headers) as a beta option for custom connectors. Add the deployed /mcp URL under Customize → Connectors → Add custom connector (Team/Enterprise owners add it under organization connector settings). In advanced/request-header settings add:

Authorization: Bearer <the exact PANEL_BEARER_TOKEN value>

Then connect/enable Panel in the target Claude conversation. Do not put the token in the URL.

If the request-header field is not exposed for your account, do not make this server public without auth. That account/UI has not enabled the beta static-header path; OAuth would then be a separate, explicitly required follow-up.

Verification harness behavior

npm run manual invokes all four providers through MCP using one conversation_id. Its DeepSeek, Kimi, and Gemini prompts explicitly require reactions to earlier named providers, making shared transcript behavior visible. npm run verify:persistence writes through one PostgreSQL pool, closes it, creates a fresh pool, and reads the sentinel back. The compaction unit test confirms the request rendering is compacted while the original full turn array remains unchanged; the PostgreSQL transcript is only read during rendering.