MSIO
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., "@MSIOLook at jobs completed in the last 4 months and tell me which zip codes have the most activity."
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.
MSIO — HCP Tools for AI Agents
Madam Secretary Intelligent Operations (MSIO) is an MCP server built to assist plumbing company operators who use Housecall Pro (HCP) daily. Running it as an MCP server means operators work through the AI chat interface they are already familiar with, leveraging the power of a cloud-based subscription AI they already pay for. The purpose of MSIO is to give AI agents useful tools to do useful work by enabling them to interact with HCP. It is in daily production use at a working plumbing company.
What it can do
MSIO gives your AI agent the ability to do the tasks that make management, evaluation, and projections easier. Most AI agents are innately good at pattern recognition, but they lack the tools to interact properly with HCP — and they lack context. MSIO provides the functions to search job history and parse information so the AI agent can read it and find the patterns. For instance, you could give it a job like:
"Look through the jobs completed over the last 4 months. Find out which zip codes have the most activity, what types of jobs we've done, and which tech has been the most efficient with their time."
The server exposes 36 tools: reading HCP data (jobs, customers, estimates, invoices, employees, tags, leads), spotting problems (stale estimates, uninvoiced jobs, overdue receivables), business intelligence (customer history and risk signals, tech performance, revenue forecasting, job classification), estimate generation, and a small set of validated write operations (tags, notes, line items, scheduling).
Related MCP server: housecallpro-mcp
Architecture
When the MCP server connects to the user's agent, it provides the agent with descriptions of its tools for selection when needed. A user request triggers the agent to select a tool based on reasoning. The agent forms the client request for the appropriate tool, structured as MCP over stdio. app.py routes the request to that tool's handler, which validates the inputs and then calls HCP's REST API through hcp_client.py. Structured JSON is returned from HCP, parsed into a consistent response envelope (success / data / error / metadata, with credentials redacted), and given back to the agent. The agent then reads the information and forms the response that is given to the user.
Reasoning happens at the two ends of that chain — tool selection and the final answer — and everything in the middle is deterministic Python. The server makes no LLM calls of its own: it either works or returns a structured error, and it cannot hallucinate.
Much of the deterministic layer exists because HCP's API behaves in ways the docs don't advertise. Every monetary amount arrives in cents. Estimates are write-once — no update, no delete. And POST /jobs returns a 201 success while silently dropping the job's description field; the server works around it by creating the job, then attaching the description as a note in a second call. Each gotcha like this is encoded once in the execution layer so no user — human or AI — ever hits it again.
Install and configuration
MSIO's intended use is with Claude Desktop, and the directions below reflect that — it's what the server was built and tested against. Because it's built on the open MCP standard, any MCP-compatible agent is viable, including private/self-hosted agents; installation and configuration guides for those will be added in future updates.
Requires Python 3.11+ and uv. An HCP API key is only available on plan tiers that include API access (e.g. MAX) — find it in your HCP settings, where you will have HCP generate a key.
git clone https://github.com/brystal00/msio-server
cd msio-server
uv venv .venv --python 3.13
uv pip install -e ".[dev]"
make checkThen register the server in your Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"madam-secretary": {
"command": "/path/to/msio-server/.venv/bin/python",
"args": ["/path/to/msio-server/server.py"],
"env": { "HCP_API_KEY": "your_key_here" }
}
}
}Restart Claude Desktop, approve the MCP connection, and Claude will have access to the tools. (A double-click install bundle for non-technical users is planned.)
Status and scope
This application is completely local stdio. This is deliberate: it keeps access to your HCP account and your data centralized to your computer — there is no hosted service, no third-party server, and nothing to sign up for. It is important to note that if you use a cloud-model AI agent, your data will flow through their cloud servers accordingly.
License
Licensed under the MIT License. Built on Anthropic's open Model Context Protocol standard.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
Flicense-qualityDmaintenanceMCP server that lets AI agents execute structured business processes by exposing process steps as tools with a sequenced event bus to prevent skipping steps.1- AlicenseAqualityCmaintenanceMCP server for Housecall Pro, providing 5 tools for AI agents to register customers, schedule jobs, create estimates, log leads, and generate invoices (env-gated).5MIT
- Alicense-qualityBmaintenanceAn MCP server that enables AI agents to execute real-world actions through 10 specialized engines covering authenticated API calls, browser automation, visual QA, shell commands, file operations, job scraping, and parallel task execution.1MIT
- FlicenseAqualityCmaintenanceMCP server for Kickserv field service management that enables AI agents to read and manage customers, jobs, and invoices through natural language.7
Related MCP Connectors
MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.
OCR, transcription, file extraction, and image generation for AI agents via MCP.
Hosted MCP with 91 agent tools: X, domains, SEO, Maps, Trends, Search, YouTube, TikTok, and more.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/brystal00/msio-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server