Connections to your APIs and data
Adapters for the agreed records, documents or API endpoints, with the authentication required by the source system.
CUSTOM MCP SERVER DEVELOPMENT
MCP Server Development
I build custom MCP servers that let compatible AI clients use your business APIs, records and internal tools.
The service connects API adapters, tool definitions, authentication and deployment. Each operation has defined inputs and results, with read and write access tested in the AI client your team intends to use.
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A CONTROLLED CONNECTION TO YOUR SYSTEMS
AI application
Your MCP serverAgreed tools · Defined access
CRMDocumentsInternal APIs
MODEL CONTEXT PROTOCOL
Your APIs, exposed as tools an AI client can use.
I turn selected API operations and information sources into MCP tools for compatible AI applications. The server translates the client’s requests into the formats and authentication your existing systems require.
The project covers the server implementation, tool definitions, access rules and testing with the chosen client. You receive documentation for running and maintaining the integration.
DEFINE THE CONNECTION
What your custom MCP server includes.
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Named tools with validated inputs
Tool definitions, structured responses and understandable errors. Each tool exposes a specific operation the workflow needs.
Access and approval boundaries
Defined permissions for reading and changing data. Consequential actions can require a separate approval step in the surrounding workflow.
THE CONNECTION AT A GLANCE
Your systems. Defined tools. Compatible AI clients.
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Your business systems
APIs & services
Existing endpoints and the operations selected for the connection.
Data & documents
The information the server is permitted to expose.
The MCP server
A defined contract for AI tools.
A custom connection between your systems and compatible MCP clients.
- Tool names and input schemas
- Authentication and access rules
- Structured responses and errors
Compatible AI clients
Discover & call tools
Clients can find the available operations and their expected inputs.
Receive a clear result
Validated responses or useful errors explain what happened.
Read access
Retrieval operations return the agreed information within the defined access scope.
Write actions
Operations that change data have separately agreed permissions and approval requirements.
READ ACCESS IS NOT WRITE ACCESS
Read and write operations are scoped separately.
I define which records can be read, which updates can be prepared and where approval is needed. Input validation and error handling are part of the implementation, alongside the working connection.
Planning the wider rollout? Explore AI transformation
Example operationBoundary to define
Find an approved documentAllowed sources and user access
Read a CRM recordAuthentication and relevant fields
Prepare a record updateValidation and approval before a write
The tool list follows your business requirements. Each operation specifies what it accepts, what it returns and which permissions it requires.
SCOPE & OPTIONS
Tools built around the operations your AI client needs.
Connect your AI client to the systems people use every day: customer records, internal documentation and operational updates. Each use case becomes a small set of tools with its own inputs, permissions and expected result.
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Customer & order lookups
Retrieve the customer, order or booking details needed for an enquiry, using a permitted identifier.
- Validate IDs and search inputs
- Respect the source system’s authentication
- Return relevant fields and clear not-found results
Company knowledge & documents
Retrieve approved documentation, product information or internal records with enough context for the client to use them.
- Connect the permitted information sources
- Limit exposed fields and records
- Include source references where available
Controlled record updates
Create or update a record through a separate write tool, with validation and approval rules defined for the workflow.
- Validate the proposed change
- Check write permissions and approval requirements
- Report the applied result or a useful failure
A REVIEWABLE INTEGRATION PROJECT
From API review to a tested MCP connection.
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Review the API and client
Check API documentation, authentication, required operations and the capabilities of the chosen AI client.
Build tools and server behaviour
Implement the adapters, tool schemas, validation and responses for the agreed scope.
Test and document the connection
Check expected requests, invalid inputs, access failures and API errors. Document configuration and operation for handover.
WHAT’S INCLUDED
What’s included in MCP server development.
You receive a working integration from the source API to your chosen compatible AI client. The proposal names the tools, access rules, deployment environment, test cases and handover materials.
API & client requirements
Review the AI client, source-system documentation, authentication and operations the integration needs.
Source-system adapters
Implement connections to the records, documents or API endpoints.
Tool definitions & validation
Define tool names, input schemas, required fields and validation for each operation.
Structured responses & errors
Return useful results and understandable responses for invalid requests, missing data or unavailable services.
Permissions & read/write boundaries
Make the allowed records and operations explicit, with approval requirements defined in the surrounding workflow.
Tool & client testing
Check expected requests, invalid input, access failures and the agreed tools in the chosen client.
Configuration & running instructions
Local or remote setup for the chosen client, environment settings, hosting responsibilities and source-system credentials kept outside public code.
Code & operating documentation
Provide the server implementation, tool descriptions, dependencies and handover instructions.
WHY WORK WITH ME
Why build your MCP integration with me.
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Work directly with me. No middlemen.
The developer reviewing your API also builds the server and checks it in your chosen client. You can discuss an operation from its business purpose through to its implementation.
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Tools designed around your operations
Inputs, returned fields, validation and permissions are defined for each tool. Lookups and updates remain separate, making it clear what the AI client can read or change.
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A server your team can run
Client checks, understandable errors and configuration guidance are included in the defined build. The handover covers deployment and dependencies so the integration can be operated beyond a demo.
Get a scope for your MCP server.
Send the AI client you want to use, the systems it should connect to and the operations it needs. API documentation will help define the tools and access requirements.
BEFORE THE FIRST MESSAGE
Questions about a custom MCP server.
Do we need a custom MCP server or an existing connector?
We check the chosen AI client, required systems and operations first. An existing maintained connector may cover the task. A custom server makes sense when you need your own tools, data boundaries or business-specific operations.
Can it connect to a private API or internal system?
Yes, when the API, authentication and network access support the required operations. I review the documentation and existing permission model before defining which records and actions the server can expose.
Which AI clients will the server work with?
The intended clients and connection method are named in the scope and tested during implementation. Client capabilities differ, so compatibility is checked against the actual tools and environment your team plans to use.
Can tools change records as well as read them?
Read tools and write tools are defined separately. A lookup might return a booking; a different operation can prepare or apply a permitted update. Inputs, user permissions and any approval step are explicit parts of that workflow.
Where does the server run?
The setup depends on who uses it and how the client connects. A local server can suit an internal developer workflow; a remotely hosted server can serve approved users over the network. Hosting, authentication and operating responsibilities are confirmed before build.
What do you need to estimate the project?
The intended client, API documentation, authentication method, required operations and deployment environment. The number and complexity of tools, access rules and testing requirements determine the scope and estimate.
What is handed over, and what if the API changes?
The handover includes the server materials, tool descriptions, configuration and operating guidance specified in the proposal. Future source-API or client changes can require updates; maintenance and compatibility reviews can be planned as a separate backlog.
06 / YOUR NEXT BIG MOVE
Let’s define the connection you need.
Tell me which AI application and business tools you want to connect, and what the connection should do. I’ll review the integration scope and reply by email.
Let’s talk.
What happens after your message
- 01 You share the goal.
- 02 I review it and reply personally.
- 03 We agree on a useful next step.