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MCP development company
The Model Context Protocol lets an AI agent call your systems through a standard interface. A useful MCP server exposes few, well-described tools, checks who is calling, limits what each tool can do and logs everything. We build those and keep them working.
Free 30-min call. No pitch, no slides.
Priced per project and scoped after a short discovery call.
Built for a sample of 40+ named companies. See the client list.
Quick answer
AY Automate builds production Model Context Protocol (MCP) servers that give AI agents scoped, authenticated and logged access to internal systems, databases and APIs, with testing and maintenance. Typical timeline: two to five weeks for a first server, scoped after the discovery call. Priced per project and scoped after a short discovery call.
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What it is
MCP is a protocol, not a product. The value is in the design of the server: which tools it exposes, how they are described so a model picks the right one, what each is allowed to touch, and what happens on failure.
Public examples often expose a whole API as tools. That floods the model with choices and gives it more power than the task needs. We design narrow tools around real jobs, such as look up an order or draft a reply, and enforce limits on the server side.
We work at the server and integration level, and connect it to clients such as Claude and Claude Code. We do not claim to run a hosted MCP marketplace.
Fit check
Teams giving agents access to internal systems
Databases, ticketing, CRMs and internal APIs exposed through a controlled interface.
SaaS products wanting an official MCP server
So customers can use your product from Claude and other MCP clients.
Teams standardizing many ad-hoc agent integrations
One maintained server instead of a dozen one-off scripts.
How it works
We design the tool list first, because a bad tool list cannot be fixed by good code.
List the real jobs agents need to do, then design the smallest set of tools for them.
DeliverableTool specification with descriptions
Decide who may call what, how identity is passed and which tools need approval.
DeliverablePermission model
Implement the server with validation, rate limits, logging and error handling.
DeliverableWorking MCP server
Run real tasks through Claude and other clients, and tune descriptions where the model chooses wrong.
DeliverableTest report and tuned tool set
Deploy with monitoring, and keep it current as the protocol and your systems change.
DeliverableDeployed server and maintenance plan
Typical timeline
Two to five weeks for a first server, scoped after the discovery call
Stack we build with
MCP · TypeScript · Python · Claude · Claude Code · PostgreSQL · OAuth · Docker
Use cases
Agents answer questions from databases with role-scoped results.
Narrow tools to look up records and draft updates for approval.
An official server so customers can use your product from their AI client.
First 30 days
A working server with a small, tested tool set.
Week 1
The jobs, the tools and the descriptions, reviewed with the people who will use them.
Week 2
Which identities can call which tools, and which tools need a person to approve.
Week 3 to 4
Deployed to a test environment with logging and rate limits on.
Day 30
Real tasks run through Claude, with tool descriptions tuned where the model chose wrong.
Scope
Results
These are outcomes where agents were given controlled access to business data. They show the access pattern, not a claim that each used MCP.
The whole database became an agent anyone can talk to. Each person gets their own scope and only sees and generates reports and charts for what they are allowed to touch.
Meetings are recorded and turned into text automatically, documents are read and filed without re-typing, and client updates reach the right notary the moment they happen.
A fully branded client-facing platform with automatic candidate to opportunity matching, and security and access control built in from day one rather than added afterwards.
Pricing
Priced per project and scoped after a short discovery call, not sold as a fixed package. Cost follows the number of systems, the access model and the security requirements.
Scoped after a discovery call
Most engagements start with one narrow, high-value piece so you see it running in production before anything expands.
From $60,000/year
A dedicated engineer building and maintaining the work inside your team, instead of a scoped project.
Free 30-min call. No pitch, no slides.
A 30 minute call. We look at the systems and the jobs and tell you which tools are worth exposing and which are not.
In this call, we'll walk through your project scope, timeline, and goals - so we can both check if we're a fit. No obligation, no slide deck, just a working session.
Don't want a call? Email walid@ayautomate.com
“The team is super fast - sometimes we had to slow them down. We managed to scale the company without investing into hiring.”

Elie Salame
COO, Adstronaut.io
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FAQ
The Model Context Protocol is an open standard that lets AI clients such as Claude call external tools and read external data through one consistent interface.
Too many tools confuse the model and give it more power than the task needs. We design a few narrow tools around real jobs and enforce limits on the server.
Security comes from the server design: authentication, per-tool permissions, validation and logging. Use the Claude Code security audit if you also want your client-side setup reviewed.
Priced per project and scoped after a short discovery call. Cost follows the number of tools, the systems behind them and the access model.
We can under a maintenance plan, covering protocol updates, dependency updates and fixes when your systems change. Or your engineers take it over from our documentation.