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AI Engineering

MCP & Tool Integration

Give the model a safe way to act

The hard part of tool use is not the call, it is the contract: what the tool accepts, what it guarantees, who may invoke it and what happens when it fails. We build MCP servers and tool layers over your internal systems so any assistant — yours, or Claude and ChatGPT in your team's hands — can use them safely, with scoped credentials and an audit trail for every invocation.

integration surfacetyped · scoped · audited
crm
erp
billing
warehouse
email
storage
auth
analytics

every call logged with actor, arguments and result

what you get
  • MCP servers exposing your systems as typed, documented tools
  • Per-tool authentication, scoping and rate limits
  • Idempotency and rollback for anything that writes
  • Audit log of every invocation with actor, arguments and result
  • Test harness so tools are verified independently of any model
how we build it
  1. 01

    Inventory the surface

    Which operations are genuinely safe to expose, and under whose authority.

  2. 02

    Type the contract

    Schemas, examples and failure modes, written for a model to read.

  3. 03

    Audit everything

    Every call is attributable after the fact — that is what makes this deployable.

stack
MCPTypeScriptPythonOAuth 2.0OpenAPIPostgres

Model Context Protocol is an open standard for exposing tools and data to AI assistants over a consistent interface. Build the server once and any MCP-capable client can use it, instead of writing a bespoke integration per assistant.