Custom MCP servers
Custom MCP Servers for Claude & ChatGPT
Claude and ChatGPT can’t touch your CRM or database — until you give them tools that live on your side.
For agency and SMB founders whose team already lives in Claude or ChatGPT, but every useful answer still ends with “someone has to check HubSpot / Postgres / Notion.” Done looks like: you ask the model to find the deal, update the stage, or pull the row — and it does, against your real systems, without pasting CSVs into chat.
Before → after
Deal update in the middle of a call
Before
Rep asks Claude for context → copies deal ID from HubSpot → pastes notes back by hand → stage stays stale until someone remembers.
After
Rep asks Claude → MCP searches HubSpot → updates stage and next step → Slack gets a one-line summary. Credentials never leave your server.
What an MCP server actually is
Model Context Protocol (MCP) is a standard way to give an AI assistant tools it can call on your behalf. Instead of copying data into the chat window, the model invokes something you control — search contacts, write a deal, run a Postgres query — and gets structured results back. The server sits next to your stack; Claude Desktop, ChatGPT with connectors, or Cursor talk to it over that protocol.
You are not buying another SaaS dashboard. You are shipping a small, production service that exposes only the tools your team should have, with auth and credentials that stay on your infrastructure.
What tools you’d expose
Typical first tools:
- Search HubSpot contacts and companies
- Create or update deals
- Pull a Notion page
- Post a Slack summary
- Run a parameterized Postgres query
- Look up an order or ticket by ID
We scope the allow-list with you — the model should never get a raw “run any SQL” button unless you explicitly want that.
Claude Skills sit on top: short instructions that teach the model when to call which tool, how to confirm destructive writes, and how to format answers your team already expects.
When Zapier is enough vs when you need MCP
Zapier (or Make / n8n) wins when the trigger is fixed and rare: “new Typeform → create HubSpot contact → Slack ping.” Nobody is mid-conversation asking questions.
MCP wins when a human is already talking to the model and needs live read/write into the CRM or database — branching judgment, lookups, and follow-up questions in the same thread. Glue tools break on messy auth, partial records, and “it depends” branches; a purpose-built MCP server handles those paths with explicit tools and logging.
We are the team that ships a production MCP server in 1–2 weeks — not a weekend tutorial cloned from a blog post.
What we build and what this is not
What we build
- A production MCP server wired to the systems you already use — HubSpot, Postgres, Notion, Slack, and internal REST APIs
- Tool definitions scoped to real jobs: search contacts, write deals, query rows, draft Slack updates
- Auth and credentials hosted on your side (or your VPC) — keys never sit in a public chat product
- Claude Skills / system prompts so the model knows when to call which tool and when to ask before writing
- Logging and a short handoff so your team can extend tools without starting over
What this is not
- Not a hosted “AI CRM” you migrate into
- Not Zapier with an LLM badge slapped on
- Not an open-ended agent with root access to your database
- Not a blog tutorial or demo repo left for you to productionize
FAQ
Will this work with the Claude / ChatGPT we already pay for?
Yes. We build against the MCP clients your team actually uses (Claude Desktop, compatible ChatGPT setups, Cursor, and similar). The point is your existing assistants talking to your systems — not forcing a new chat product on the team.
Where do API keys and database credentials live?
On your side. The MCP server runs in your environment (or a project you control). We never need your HubSpot or Postgres keys sitting in a third-party chat product.
Can the model delete or overwrite data?
Only if you allow that tool. Default builds separate read tools from write tools, require confirmation on destructive actions, and log every write so you can see what happened.
We already have Zapier. Do we rip it out?
No. Keep Zapier for fixed trigger → action flows. Use MCP for conversational, mid-work lookups and updates. The audit tells you which jobs belong where.
How long does a first MCP server take?
Most first production servers ship in 1–2 weeks after the audit scopes the tool list and systems. Bigger custom platforms take longer and land under Custom AI OS.
Book the audit
If this job is yours, start with the $499 AI Opportunity Audit. We map the workflow, name the stack, and credit the fee toward the build.
Book Your $499 Audit