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., "@MCP Teamtailor list candidates created in the last week"
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.
The MCP Teamtailor is a Model Context Protocol (MCP) server that provides a simple integration with the teamtailor api.
No other dependencies are required to use the MCP Teamtailor server.
Related MCP server: Greenhouse MCP Server
MCP servers are configured differently depending on the client that you are using. For reference, this is how you would configure it using Claude Desktop.
{
"mcpServers": {
"teamtailor": {
"command": "npx",
"args": [
"-y",
"@crunchloop/mcp-teamtailor"
],
"env": {
"TEAMTAILOR_URL": "https://api.teamtailor.com/v1",
"TEAMTAILOR_API_KEY": "XXXX"
}
}
}
}At the moment, only stdio transport has been implemented.
teamtailor_list_candidates - List and filter candidates.
pageSize: The size of the page response (string, optional)
page: The page number to retrieve (string, optional)
filter.createdAfter: Filter candidates created after a specific date (string, optional)
filter.createdBefore: Filter candidates created before a specific date (string, optional)
filter.updatedAfter: Filter candidates updated after a specific date (string, optional)
filter.updatedBefore: Filter candidates updated before a specific date (string, optional)
teamtailor_get_candidate - Get a single candidate by their id.
candidateId: The id of the candidate to retrieve (number, required)
Released under the MIT License. See the LICENSE file for further details.
Get a single candidate by their id.
| Name | Required | Description | Default |
|---|---|---|---|
| candidateId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states 'Get' with no details on response format, side effects, permissions, or rate limits. For a read operation, more context would be beneficial.
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 a single, front-loaded sentence with no superfluous words. It efficiently conveys the core function.
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 simple one-parameter tool and no output schema, the description is minimally complete. It states what the tool does but lacks details about the response or any edge cases, which could be helpful for a complete understanding.
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 coverage is 0%, and the description adds minimal meaning ('by their id') beyond the parameter name 'candidateId'. No format, constraints, or examples are given, but the purpose is partially clarified.
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 (Get), resource (candidate), and qualification (by id). However, it does not distinguish from sibling tool 'teamtailor_list_candidates' beyond the implied singular vs. plural.
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 that use is for retrieving a specific candidate by ID, but no explicit guidance on when to use this versus the list tool, or any prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List and filter candidates.
| Name | Required | Description | Default |
|---|---|---|---|
| pageSize | No | ||
| page | No | ||
| filter | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It does not disclose any behavioral traits such as pagination behavior, rate limits, or what happens when filters yield no results. The tool's mutability is unclear.
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 short (4 words) but this is not conciseness; it is under-specification. Important details about parameters and behavior are omitted. A concise description would still cover essential aspects.
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 (nested filter object, pagination, no output schema), the description is completely inadequate. It does not explain return values, filtering syntax, or any other context needed for correct invocation.
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 schema has 0% description coverage, and the description adds no parameter details. It mentions 'filter' but does not explain the filter object's properties (createdAfter, etc.) or how pagination parameters work. This is insufficient for proper 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 states the tool lists and filters candidates, which is a clear verb+resource. However, it does not differentiate from the sibling 'teamtailor_get_candidate', which likely retrieves a single candidate. The purpose is clear but lacks specificity.
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?
No guidance is provided on when to use this tool versus alternatives. The sibling tool exists but is not mentioned, and there is no context about appropriate scenarios or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The two tools have clearly distinct purposes: one retrieves a single candidate by ID, the other lists and filters candidates. There is no ambiguity.
Both tools follow a consistent verb_noun pattern with the prefix 'teamtailor_', making them predictable and easy to understand.
With only 2 tools, the set feels thin for a typical ATS domain. While basic get and list are covered, a richer set (e.g., create, update, delete) is expected, making the count borderline.
The tool surface is severely incomplete for candidate management: it lacks create, update, delete operations, and other common entities like jobs or applications are missing.
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If you are the server author, to access and configure the admin panel.
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