basecamp-mcp-server
MCP server for Basecamp 5 that gives AI assistants access to projects, to-dos, messages, campfire chat, documents, and card tables.
README
basecamp-mcp-server
An MCP server for Basecamp 5 — gives your AI assistant access to projects, to-dos, messages, campfire chat, documents, and card tables.
Works with Claude Code, Claude Desktop, Cursor, OpenAI Codex, and VS Code.
You: What's on my plate in Basecamp this week?
→ basecamp_my_assignments
→ Two things are assigned to you, both in Fieldwork Study:
• Send Robin the drafted survey instrument — due today, 2 subtasks
• Review the pilot analysis — due Friday
Requirements
- Python 3.11+
- A Basecamp 5 account
- Credentials, via either:
- the Basecamp CLI — recommended, because it keeps a self-refreshing OAuth token in your OS keyring and this server never touches your disk; or
- a
BASECAMP_ACCESS_TOKENenvironment variable (expires after 14 days, with no refresh)
Quick start
# 1. Authenticate, if you have not already
basecamp auth login
# 2. Check that everything resolves — this makes a real API call
uvx basecamp-mcp-server doctor
# 3. Add it to your client (Claude Code shown; others below)
claude mcp add basecamp -- uvx basecamp-mcp-server serve
doctor prints the resolved credential source, your Basecamp accounts, and a paste-ready config
block for every supported client. Start there if anything below does not work.
Client configuration
The formats genuinely differ between clients — the key name, the file, and whether it is JSON or TOML. Copy the one you need.
Claude Code
claude mcp add basecamp -- uvx basecamp-mcp-server serve
Verify with claude mcp list; it should report ✔ Connected.
Claude Desktop
claude_desktop_config.json — macOS ~/Library/Application Support/Claude/,
Windows %APPDATA%\Claude\:
{
"mcpServers": {
"basecamp": {
"command": "uvx",
"args": ["basecamp-mcp-server", "serve"]
}
}
}
Cursor
.cursor/mcp.json in the project, or ~/.cursor/mcp.json globally. Same mcpServers shape as
Claude Desktop.
VS Code
.vscode/mcp.json. Note the key is servers, not mcpServers, and type is required:
{
"servers": {
"basecamp": {
"type": "stdio",
"command": "uvx",
"args": ["basecamp-mcp-server", "serve"]
}
}
}
OpenAI Codex
~/.codex/config.toml — TOML, and the table is mcp_servers with an underscore:
[mcp_servers.basecamp]
command = "uvx"
args = ["basecamp-mcp-server", "serve"]
Permissions
The server has three modes. Tools you have not enabled are not registered at all, so the model never sees them and never proposes an action you have forbidden.
| Mode | Flag | Tools | What it can do |
|---|---|---|---|
| Read-only | --read-only |
19 | Look at everything; change nothing |
| Default | (none) | 28 | Create and edit; remove nothing |
| Full | --allow-destructive |
29 | Also trash and archive, and only with confirm: true |
# See exactly what a given configuration exposes
uvx basecamp-mcp-server tools list --read-only
Read-only is worth considering if you mainly want your assistant to answer questions about Basecamp. You can always restart with writes enabled.
What it can do
Find things — list_projects · get_project · search · my_assignments · list_people
To-dos — list_todolists · list_todos · get_todo · create_todo · update_todo ·
complete_todo
Messages and chat — list_messages · get_message · create_message · list_comments ·
create_comment · list_campfire_lines · create_campfire_line
Docs and cards — list_documents · get_document · get_card_table · list_cards ·
create_card · move_card
Anything else — basecamp_request reaches any Basecamp endpoint these tools do not cover
(GET only), and basecamp_write_request covers POST and PUT.
Start with basecamp_get_project: it returns a tools map giving the ids every other tool in
that project needs, so your assistant does not have to guess them.
Configuration
Everything is optional; the defaults are chosen to be safe rather than fast.
| Variable | Default | Notes |
|---|---|---|
BASECAMP_ACCESS_TOKEN |
— | Only needed without the Basecamp CLI |
BASECAMP_ACCOUNT_ID |
auto | Required only if you belong to several Basecamp accounts |
BASECAMP_MCP_READ_ONLY |
false |
Same as --read-only |
BASECAMP_MCP_ALLOW_DESTRUCTIVE |
false |
Same as --allow-destructive |
BASECAMP_MCP_USER_AGENT |
this project | Must contain a contact URL or email, or Basecamp rejects every request with a 400 |
BASECAMP_MCP_MAX_PAGES |
25 |
Upper bound on auto-pagination per call. Capped at 200 |
BASECAMP_MCP_MAX_RESULT_CHARS |
25000 |
Size ceiling for one tool result |
BASECAMP_MCP_LOG_LEVEL |
INFO |
Logs go to stderr, never stdout |
Notes
Responses are projected, not passed through. Basecamp payloads are built for a rich web client: one to-do is ~5 KB of JSON and a single message can be 37 KB. Unprojected, a hundred to-dos would be around 530 KB — enough to end a conversation. Every response is reduced to the fields that let a model answer and chain to the next call, which is a 12–60× cut depending on type, with every id preserved.
Content from Basecamp is untrusted input. To-do titles, message bodies and comments are written by other people. The server tells your assistant to treat them as data to report on rather than instructions to follow, but that is a mitigation, not a guarantee — bear it in mind before enabling writes on an account with people you do not know.
Edits preserve fields you did not mention. update_todo reads the record, overlays your
changes and writes it back, so setting a due date does not erase the assignees. The cost is that
it is two requests rather than one, and a concurrent edit in between is overwritten.
Development
uv sync
uv run ruff check . && uv run ruff format --check . && uv run mypy && uv run pytest
See AGENTS.md for architecture, layer rules, and a list of verified upstream behaviours that look like bugs until you read the source.
License
MIT — see LICENSE.
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
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.
E2B
Using MCP to run code via e2b.