Outcome
A documented MCP/tool layer with clear capabilities, inputs, outputs, validation, error handling, permission boundaries, and usage examples.
Give agents structured access to real tools
MCP server for internal APIs
Reduce brittle prompt-only automation
Agent access to files, databases, or dashboards
Control what the agent can read or change
CRM, CMS, or admin tool connector
Improve debugging with clear inputs, outputs, and errors
Automation backend for LangGraph agents
What you receive
- Tool capability map
- MCP server or tool layer implementation
- Schemas and validation logic
- Connector handlers
- Error handling and basic tests
- Usage documentation and examples
Methodology
- Define allowed tools and actions
- Design schemas, inputs, and outputs
- Build handlers and connector logic
- Add validation, errors, and permission boundaries
- Test tool calls with example cases
- Document usage for agents and developers
Scope
Includes one MCP server or tool integration layer, tool schema design, handlers, input validation, API/database/file connector logic, error handling, basic tests, and usage documentation. This service focuses on tool access, not designing the whole agent experience unless combined with agent development.
Details
What to expect from this engagement
What is included?
I build MCP servers and structured tool layers so AI agents can interact with real systems in a controlled way. This includes schemas, handlers, validation, permissions, error handling, and documentation for how tools should be used.
Who is it for?
Teams building agents that need reliable access to tools, APIs, databases, files, or internal systems.
What do you need to provide?
Requires access to target APIs, internal tools, files, database schema, credentials or sandbox keys, and a list of allowed actions. Does not include broad product UI, unrelated backend refactors, or enterprise permission systems unless scoped separately.