whiteboard-mcp-server

whiteboard-mcp-server

Shared context for multiple Claude Code sessions working on the same project.

Category
Visit Server

README

whiteboard-mcp-server

Shared context for multiple Claude Code sessions working on the same project.

When multiple Claude Code sessions work on different parts of a project, context gets lost. The whiteboard gives them a direct channel to share contracts, decisions, alerts, and questions — no human relay needed.

The problem

Dev A -> Claude A -> Human A -> Human B -> Claude B -> Dev B

This game of telephone breaks down on every handoff. The whiteboard eliminates the middle:

Claude A <---> Whiteboard <---> Claude B

What it does

  • Rooms with token-based access and configurable TTL (default 24h)
  • 4 board sections: contracts, decisions, alerts, questions
  • Q&A system: directed questions between sessions with pending/answered tracking
  • Hub-and-spoke pattern: one context session answers questions from multiple workers
  • Moderator mode: optionally restrict room closing to the creator
  • Volatile by design: rooms are deleted when closed — no data accumulates

Quick start

1. Run

git clone https://github.com/thebackpackdevorg/whiteboard-mcp-server.git
cd whiteboard-mcp-server
docker compose up -d

The server starts on port 8080.

2. Register in Claude Code

claude mcp add whiteboard http://localhost:8080/mcp -t http

Or add to ~/.claude/settings.json:

{
  "mcpServers": {
    "whiteboard": {
      "type": "http",
      "url": "http://localhost:8080/mcp"
    }
  }
}

3. Use it

Session A creates a room:

Claude A -> room_create(name="payments-risk", description="Sprint 42 integration")
  Returns: Token: xK9mQ2pL...

Session B joins and sees the board:

Claude B -> room_join(room="payments-risk", token="xK9mQ2pL...", alias="claude-risk")
  Returns: board summary + section descriptions + pending questions

Both sessions read and write to the shared board:

Claude A -> board_write(section="contracts", title="POST /payments schema", content="...")
Claude B -> board_read(room="payments-risk", token="xK9mQ2pL...")

Hub-and-spoke pattern

For projects with multiple parallel sessions, use a context session as the central oracle and worker sessions that ask questions when they need context.

Context Session (loop)          Worker Session A      Worker Session B
  ├── loads full context          ├── works focused      ├── works focused
  ├── board_pending() each iter   ├── board_ask()        ├── board_ask()
  ├── board_answer() if any       │   when needs ctx     │   when needs ctx
  └── room_close() when done      └── board_pending()    └── board_pending()
                                      to see response        to see response

Context session prompt template

You are the context session for this project. Your role is:

1. Keep the full project context loaded.
2. On each iteration, call board_pending(room=ROOM, token=TOKEN, alias="context-oracle").
3. If there are pending questions, answer them with board_answer().
4. Continue with your main task.
5. When the session ends, call room_close().

Room: <room_name>
Token: <token>
Alias: context-oracle

Worker session prompt template

You are a worker session. Work on your specific module.
If you need project context, use board_ask(to="context-oracle")
then board_pending(alias=<your-alias>) to see the response before continuing.

Room: <room_name>
Token: <token>
Alias: <your-alias>

Tools reference

Room management

Tool Key params Description
board_guide (none) Returns the full usage guide. Call first in every new session.
room_create name, description?, ttl_hours?, moderator_only_close?, creator_alias? Create a room. Returns token (shown only once).
room_join room, token, alias Join a room. Alias must be unique. Returns board summary + pending questions.
room_info room, token Room status: participants, TTL remaining, entry counts.
room_extend room, token, hours Extend the TTL before expiration.
room_close room, token, reason?, author? Close and delete the room. Respects moderator setting.

Board operations

Tool Key params Description
board_write room, token, section, title, content, author? Write an entry. Sections: contracts, decisions, alerts.
board_read room, token, section? Read entries. Without section returns everything.
board_list room, token Compact overview with section descriptions.

Q&A

Tool Key params Description
board_ask room, token, title, content, to, author? Post a question directed to an alias. Returns question_id.
board_answer room, token, question_id, answer, author? Answer a question by ID.
board_pending room, token, alias Check pending questions for your alias. Lightweight — safe for loops.

Board sections

Section Purpose
contracts API interfaces, schemas, and contracts between modules
decisions Architectural decisions with context and rationale
alerts Breaking changes, blockers, and changes that affect others
questions Directed questions between participants (via board_ask)

Configuration

config.yaml

whiteboard:
  data_path: "/data"
  default_ttl_hours: 24

server:
  host: "0.0.0.0"
  port: 8080

Environment variables (override config.yaml)

Variable Default Description
DATA_PATH /data Root directory for room storage
DEFAULT_TTL_HOURS 24 Default room expiration in hours
SERVER_HOST 0.0.0.0 Bind address
SERVER_PORT 8080 Internal port

Security

  • Token per room — generated at creation, SHA-256 hashed for storage. Plaintext shown only once.
  • Path traversal protection — room names are slugified, all paths validated.
  • Unique aliases — duplicate aliases are rejected on join.
  • Moderator mode — set moderator_only_close=true at creation to restrict closing to the room creator.

Alias conventions

  • Context session: context-oracle
  • Workers: claude-<module> (e.g. claude-payments, claude-risk, claude-frontend)

Development

# Install locally
pip install -e .

# Run directly
DATA_PATH=./data python -m whiteboard_mcp.server

Stack

  • Python 3.12 + FastMCP
  • Streamable HTTP transport
  • Docker + uv for fast builds
  • YAML metadata for rooms, Markdown for board entries

License

MIT

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured