Greenhouse MCP

read_candidate_resume

Retrieve a candidate's most recent resume text by candidate ID for recruiting review. Search by name to find the ID; returns extracted text from the latest uploaded resume.

Instructions

Download and return a candidate's most recent resume text. Read-only.

Users say "pull up Sarah's resume" or "show me John's CV." To find candidate_id: search_candidates_by_name. Returns extracted text from the most recently uploaded resume across all the candidate's applications. For batch reading, use batch_read_resumes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "candidate_id": "<candidate_id>"
    },
    "name": "read_candidate_resume"
  }
}

Input Schema

Name	Required	Description	Default
`candidate_id`	Yes	Greenhouse candidate ID

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.5.0Oct 5, 2026
- addedInput schema / properties / candidate_id / description
```
Added value: +"Greenhouse candidate ID"
```
Addedv0.3.4Apr 15, 2026

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does well: it declares 'Read-only' and discloses the selection behavior ('most recently uploaded resume across all the candidate's applications'), which is non-obvious. It doesn't cover auth/permission requirements or rate limits, but the key behavioral traits are stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core action and scoping constraint, then adds example phrasings and routing hints. Efficient overall, though the user-utterance examples ('pull up Sarah's resume') are somewhat decorative and could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value explanation is unnecessary; the description still notes that extracted text is returned. It fully covers the single parameter's provenance and the alternative tool, leaving no gaps for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the candidate_id type and description are already documented (baseline 3). The description adds real value by routing the agent to search_candidates_by_name to resolve the ID, going beyond the schema's bare 'Greenhouse candidate ID'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (download/return) and resource (candidate's most recent resume text), and explicitly distinguishes itself from sibling tools batch_read_resumes and download_attachment. An agent can tell it apart from other read tools without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance, including how to obtain the required candidate_id ('To find candidate_id: search_candidates_by_name') and the alternative for bulk operations ('For batch reading, use batch_read_resumes'). Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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