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Homerun MCP Server
for AI Agents
Connect your AI agent to StackOne's Homerun MCP server and give it ready-to-use MCP tools out of the box. Auth, tool execution, and security all managed.
Homerun MCP Server
Built by 
StackOne
StackOne 
Coverage
11 Agent Actions
Create, read, update, and delete across Homerun — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Homerun MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Homerun tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Homerun call.
Tools Discovery →What is the Homerun MCP Server?
A Homerun MCP server lets AI agents read and write Homerun data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Homerun MCP server ships with pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Homerun MCP Tools
Every action from Homerun's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Job Applications
- Create Job Application
Create a new job application in Homerun.
- List Job Applications
Retrieve a paginated list of job applications with optional filtering and related data inclusion.
- Get Job Application
Retrieve a specific job application by ID.
- Update Job Application
Update an existing job application.
- Delete Job Application
Delete a job application by ID.
Vacancies
- List Vacancies
Retrieve a paginated list of vacancies with optional filtering and related data inclusion.
Vacancys
- Get Vacancy
Retrieve a specific vacancy by ID.
Notes
- Create Note
Create a note on a job application.
Files
- Upload File
Upload a file (resume or assignment) to a job application.
Photos
- Upload Photo
Upload a photo to a job application.
Pings
- Ping
Test endpoint to verify API key authentication is working.
Homerun AI Agent Use Cases
Connect your AI agent to Homerun and help your team scale the recruiting operations they run by hand today.
Job Posting Distribution
Use StackOne to connect your AI agent to your ATS and job boards to automate job posting distribution.
View Reference Check Automation
Use StackOne to connect your AI agent to your ATS, survey tools, and messaging systems to automate reference checks.
View Offer Letter Generation
Use StackOne to connect your AI agent to your ATS, HRIS, and document management tools to automate offer letter generation.
ViewSet Up Your Homerun MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Homerun in under 10 lines of code.
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Platform Resources
MCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 min
Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 min
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
MCP vs A2A: Architecture, Security, and When to Use Each
MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.
12 min
MCP vs API: What 200+ Connector Builds Taught Us
MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.
14 min read
Homerun MCP Server FAQ
Does StackOne have a Homerun MCP server?
Yes. StackOne offers a hosted Homerun MCP server, and every action is tested and QA'd by StackOne. Connect it to Claude, Cursor, and any other MCP client, or to any agent framework through the AI Action SDK. It ships with managed agent authentication, prompt injection defense, and tool discovery with server-side execution that preserve your agent's context window and keep reasoning performance.
Homerun MCP server vs direct API integration — what's the difference?
A Homerun MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Homerun. A Homerun MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Homerun at runtime. StackOne provides both.
How does Homerun authentication work for AI agents?
Homerun authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Homerun account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via
origin_owner_id.Are Homerun MCP tools vulnerable to prompt injection?
Yes — Homerun MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Homerun agent and how do I avoid it?
Context bloat happens when Homerun tool schemas and API responses eat your Homerun agent's memory, preventing it from reasoning effectively. A single Homerun query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Homerun agent can access?
Yes — you can limit which actions your Homerun agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Homerun MCP server?
Yes — you can create custom agent actions for your Homerun MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Homerun's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Homerun MCP server?
Skip a Homerun MCP server if your integration is purely software-to-software — direct Homerun API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Homerun actions at runtime.
What AI frameworks and AI clients does the StackOne Homerun MCP server support?
The StackOne Homerun MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.
Put your AI agents to work
All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.