Bullhorn MCP Agent

by CaseyTTS

Overview Schema Source Related Servers Discussions Admin

Python

Remote

list_jobs

Search and filter Bullhorn CRM job orders by Lucene query, status, or limit to find open roles and hiring needs.

Instructions

List and filter job orders from Bullhorn CRM.

Args: query: Lucene search query (e.g., "title:Engineer AND isOpen:1") status: Filter by job status limit: Maximum number of results (1-500, default 20) fields: Comma-separated fields to return

Returns: JSON array of job orders

Examples: - list_jobs() - Get recent jobs - list_jobs(query="isOpen:1") - Get open jobs - list_jobs(query="title:Software AND employmentType:Direct Hire", limit=10) - list_jobs(status="Accepting Candidates")

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	No
`fields`	No
`status`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 15, 2026

TDQS

A4.5/5.0

Behavior4/5

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

No annotations provided, so description fully explains behavior: returns JSON array, supports Lucene query, defaults to 20 results. It doesn't mention pagination or permissions, but non-destructive listing is implied.

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?

Description is structured with Args, Returns, and Examples. It is concise enough for a tool with 4 parameters, though slightly verbose. Front-loaded with purpose, making it easy to scan.

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?

Given output schema exists and no annotations, description is complete: covers all parameters, provides examples, mentions defaults and return format. No gaps for this complexity level.

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

Parameters5/5

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

Schema has 0% description coverage, but description compensates fully: explains query (Lucene), status (filter), limit (max 1-500, default 20), fields (comma-separated). Examples demonstrate usage, adding significant value.

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?

The description clearly states it lists and filters job orders from Bullhorn CRM. It distinguishes from sibling tools like get_job (single job) and list_candidates (different entity), making its purpose specific.

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

Usage Guidelines4/5

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

Provides examples showing different usage patterns (no args, query, status), giving clear context. However, it does not explicitly state when not to use this tool or mention alternatives like query_entities.

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