Provides tools for managing Basecamp projects, including listing projects with detailed information, managing to-do sets and lists, accessing message boards with rendered content, and creating new to-dos with optional due dates.
Click on "Install 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., "@Basecamp MCP Server list my recent projects with their current status"
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.
A Model Context Protocol (MCP) server that exposes Basecamp tools to AI assistants (e.g., VS Code Chat in Agent mode).
Supports projects, to‑do sets/lists, messages (with rendered content), and creating to‑dos.
Projects
list_projects — rich listing (status, timestamps, purpose, client flags, bookmarks, enabled dock tools)
Pagination via HTTP Link header (exposes nextPage)
Optional raw dock objects
To‑do sets / lists
Resolves a project’s to‑do set from the project dock
get_todoset — returns to‑do set id/url; optional lists
list_todolists — lists to‑do lists for a project’s to‑do set
Messages
list_messages — resolves the project Message Board from dock, lists messages with pagination
Optional full content rendering (markdown/html/text)
get_message — fetch a single message (rendered or raw JSON)
To‑dos
create_todo — create a to‑do in a list (title, description, optional due_on)
Related MCP server: Basecamp MCP Server
src/
├─ lib/
│ └─ basecamp.ts # Basecamp client (auth refresh, requests, pagination)
├─ tools/
│ ├─ projects.ts # list_projects
│ ├─ todosets.ts # get_todoset, list_todolists
│ ├─ messages.ts # list_messages, get_message
│ └─ todos.ts # create_todo
└─ basecamp-mcp.ts # entrypoint (register tools, start stdio server)# 1) Install dependencies
npm install
# 2) Build
npm run build
# 3) (Optional) sanity check
node build/basecamp-mcp.js
# (MCP servers sit and wait on stdio; no output is expected here)Add your required values in a .env file at the project root.
This file is referenced by the MCP server configuration below.
Do not commit your
.envfile to version control.
Create .vscode/mcp.json in this project:
{
"servers": {
"basecamp": {
"type": "stdio",
"command": "node",
"args": ["${workspaceFolder}/build/basecamp-mcp.js"],
"envFile": "${workspaceFolder}/.env"
}
}
}Now restart the server from VS Code:
Command Palette → “MCP: List Servers” → basecamp → Start/Restart
Open Chat, switch to Agent, enable the basecamp tools.
Projects (JSON with dock):
Run basecamp.list_projects with { "format": "json", "dock_detail": true, "limit": 5 }or natural language
retrieve all project informationResolve to‑do set and lists:
Run basecamp.get_todoset with { "project_id": 123456789 }
Run basecamp.list_todolists with { "project_id": 123456789 }Natural language example
show todo sets and lists for project "{{prpjectName / Id}}"Create a to‑do:
Run basecamp.create_todo with { "project_id": 123456789, "todolist_id": 222222222, "content": "Kickoff", "due_on": "2025-09-30" }Natural language example
create a to-do in the "{to do list name}", titled "Update README.md"Messages (rendered content):
Run basecamp.list_messages with { "project_id": 123456789, "page": 1, "format": "markdown", "include_body": true }
Run basecamp.get_message with { "project_id": 123456789, "message_id": 987654321, "render": "markdown" }or
get all messages from TestMCP projectget content for this message "{messageId / title"Pagination: responses include
nextPagefrom the RFC5988Linkheader. Call again with{ "page": <nextPage> }.
ESM import errors: make sure your project is configured for ESM/NodeNext (standard TS/Node setup).
401/429 from API: verify tokens and reduce request volume; the client retries once on 429 using Retry-After.
No to‑do set / message board: that project may not have those tools enabled in its dock.
Create a new to-do in the given list.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| todolist_id | Yes | ||
| content | Yes | ||
| description | No | ||
| due_on | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a to-do, implying a write operation, but fails to mention critical aspects like required permissions, whether the creation is idempotent, error handling, or what the response might contain. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of a single, direct sentence that states the tool's purpose without any unnecessary words. It efficiently communicates the core action, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a write operation with 5 parameters (3 required) and no annotations or output schema, the description is incomplete. It does not address behavioral traits, parameter details, or expected outcomes, leaving the agent with insufficient context to use the tool effectively beyond its basic purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. However, it only vaguely references 'the given list' without explaining parameters like 'project_id', 'todolist_id', 'content', 'description', or 'due_on'. This adds minimal value beyond the schema, failing to clarify parameter meanings or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new to-do') and the target resource ('in the given list'), which is specific and unambiguous. However, it does not explicitly differentiate this tool from sibling tools like 'list_todolists' or 'get_todoset', which are read operations, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as whether it should be used for initial creation versus updates, or how it relates to sibling tools like 'list_todolists'. It lacks explicit context, prerequisites, or exclusions, offering only a basic statement of function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a single message by ID; render body as markdown/html/text, or return raw JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| message_id | Yes | ||
| render | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions rendering options and raw JSON return, which adds some context beyond basic retrieval. However, it lacks critical details such as error handling (e.g., what happens if the ID doesn't exist), authentication requirements, rate limits, or whether this is a read-only operation. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and front-loaded, consisting of a single sentence that efficiently conveys the core functionality. Every word earns its place by specifying the action, resource, and key parameter behavior without unnecessary elaboration. It's appropriately sized for a straightforward retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, no output schema), the description is incomplete. It covers basic purpose and rendering options but misses important contextual elements like error cases, authentication needs, or what the output looks like (beyond format options). Without annotations or output schema, the description should provide more behavioral and operational context to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds some semantic context by explaining the 'render' parameter's purpose (to specify output format as markdown/html/text/json) and implying 'message_id' identifies the message. However, it doesn't clarify 'project_id' or provide details on parameter interactions or constraints, leaving partial gaps in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('fetch', 'render', 'return') and identifies the resource ('a single message by ID'). It distinguishes from sibling tools like 'list_messages' by specifying retrieval of a single message rather than listing multiple. However, it doesn't explicitly differentiate from other potential get operations like 'get_todoset' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning fetching by ID and rendering options, suggesting it's for retrieving specific messages. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'list_messages' for multiple messages or other sibling tools for different resources. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Resolves the project's to-do set by reading the dock; can include lists.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| include_lists | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read operation ('reading the dock'), which is useful, but doesn't cover critical aspects like error handling (e.g., invalid project_id), performance (e.g., response time), or side effects. It mentions 'can include lists' but doesn't explain the default behavior or implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in a single sentence. It avoids unnecessary words, though it could be slightly more structured (e.g., separating parameter hints). Every part contributes to understanding, making it efficient but not maximally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on return values (e.g., format of the to-do set), error cases, and how 'include_lists' modifies the output. For a read tool with zero schema coverage, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only vaguely references 'include_lists' without explaining what lists are, how they relate to the to-do set, or the effect of the boolean. The 'project_id' parameter is implied but not elaborated. The description adds minimal meaning beyond the schema's structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Resolves') and resource ('project's to-do set'), and mentions the mechanism ('by reading the dock'). It distinguishes from siblings like 'create_todo' (write vs read) and 'list_todolists' (project-specific vs general listing), though it could be more explicit about the distinction. The title reinforces this clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid project_id), compare to siblings like 'list_todolists' for broader queries, or specify scenarios where including lists is beneficial. Usage is implied by the purpose but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Resolves the project's message board from the dock, then lists messages with pagination. Optionally include full content.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| page | No | ||
| limit | No | ||
| format | No | ||
| include_body | No | ||
| render | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions pagination and optional full content inclusion, which adds some context. However, it lacks critical details such as whether this is a read-only operation (implied by 'list' but not stated), permission requirements, rate limits, error handling, or what 'resolves the project's message board from the dock' entails operationally. For a tool with 6 parameters and no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that front-load the core functionality. Each sentence adds value: the first defines the action and scope, the second adds key features. There is no redundant or wasted language, making it efficient, though it could be slightly more structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no annotations, no output schema), the description is incomplete. It covers basic purpose and hints at some behaviors but omits details on parameter meanings, return values, error conditions, and operational constraints. For a tool that likely returns a list of messages, more context is needed to guide effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'pagination' (hinting at page/limit) and 'optionally include full content' (hinting at include_body), but fails to explain the purpose of project_id, format, render, or the specifics of pagination and content inclusion. With 6 parameters, this leaves most semantics unclear, falling short of adequately supplementing the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Resolves the project's message board from the dock, then lists messages with pagination.' It specifies the verb ('list'), resource ('messages'), and scope ('project's message board'), distinguishing it from siblings like get_message (singular) or list_projects (different resource). However, it doesn't explicitly contrast with siblings like list_todolists, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'project's message board' and pagination, suggesting it's for browsing multiple messages within a project. However, it provides no explicit guidance on when to use this tool versus alternatives like get_message (for single messages) or other list_* tools, nor does it mention prerequisites or exclusions. The usage is inferred but not clearly articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns id, name, status, timestamps, purpose, clients_enabled, bookmarked, and enabled dock tools. Supports pagination and JSON output.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| page | No | ||
| include_archived | No | ||
| include_dock | No | ||
| dock_detail | No | ||
| format | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool 'Supports pagination and JSON output' - useful behavioral context about output format and data handling. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation. For a listing tool with 6 parameters, this leaves important behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences that each serve clear purposes: the first specifies what data is returned, the second describes behavioral features. It's front-loaded with the core functionality. While efficient, it could be slightly more structured by separating parameter implications from output format information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers the core return data and mentions pagination/output format, but leaves many parameters unexplained and doesn't provide guidance on usage context. Given the complexity, it should explain parameter purposes and when to use this versus other list tools to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 6 parameters, the description must compensate but fails to do so. It mentions 'Supports pagination' which vaguely relates to 'limit' and 'page' parameters, and 'JSON output' which relates to the 'format' enum, but doesn't explain what 'include_archived', 'include_dock', or 'dock_detail' do. The description adds minimal value beyond what the bare schema provides, insufficient for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns id, name, status, timestamps, purpose, clients_enabled, bookmarked, and enabled dock tools' - a specific verb ('Returns') with detailed resource information. It distinguishes from siblings like 'create_todo' or 'get_message' by focusing on listing projects rather than creating or retrieving specific items. However, it doesn't explicitly differentiate from other list tools like 'list_messages' or 'list_todolists' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'Supports pagination and JSON output' which hints at usage context, but doesn't specify when to choose this over other list tools, what prerequisites exist, or any exclusion criteria. With sibling tools like 'list_messages' and 'list_todolists' available, the lack of comparative guidance is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Resolves the project's to-do set from dock, then lists its to-do lists.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'resolves the project's to-do set from dock', which hints at some internal process but doesn't clarify if this is a read-only operation, what permissions are needed, or how errors are handled. The description lacks details on output format, pagination, or rate limits, leaving significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences, but the first sentence ('Resolves the project's to-do set from dock') is unclear and doesn't contribute meaningfully to understanding the tool's purpose. The second sentence is more direct but could be more front-loaded. Overall, it's concise but includes wasted phrasing that reduces clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It fails to explain parameters, behavioral traits, or return values, making it inadequate for an agent to use the tool effectively. The vague phrasing adds confusion rather than compensating for the lack of structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It does not mention the 'project_id' parameter at all, failing to explain what it represents, how to obtain it, or its format. This leaves the parameter undocumented beyond the schema's basic type, adding no semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'lists to-do lists for a project', which clarifies the verb (list) and resource (to-do lists) with a scope (for a project). However, it includes vague phrasing like 'resolves the project's to-do set from dock', which adds confusion without clear meaning, and it doesn't explicitly differentiate from sibling tools like 'list_projects' or 'get_todoset'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning 'for a project', but provides no explicit guidance on when to use this tool versus alternatives like 'list_projects' or 'get_todoset'. There are no exclusions, prerequisites, or comparisons to sibling tools, leaving the agent with minimal context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0create_todo2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falseget_message2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falseget_todoset2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falselist_messages2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falselist_projects2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falselist_todolists2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsecreate_todoget_messageget_todosetlist_messageslist_projectslist_todolistsThe tools are mostly distinct, with clear separation between to-do, message, and project operations. However, 'get_todoset' and 'list_todolists' could be slightly confusing as both relate to to-do lists, though 'get_todoset' focuses on resolving the set while 'list_todolists' lists the lists within it, which helps mitigate overlap.
All tool names follow a consistent verb_noun pattern (e.g., create_todo, get_message, list_projects), using snake_case throughout. This predictability makes it easy for agents to understand and navigate the tool set without confusion.
With 6 tools, the count is reasonable for a Basecamp server, covering core operations like creating to-dos and listing projects. It's slightly lean but well-scoped, though it could benefit from additional tools for updates or deletions to enhance completeness.
The tools cover basic read and create operations for to-dos, messages, and projects, but there are notable gaps. For example, there are no update or delete tools for to-dos or messages, and operations like creating messages or projects are missing, which could limit agent workflows in a CRUD context.
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