MCP servers that let agents use your product, within the limits you set.
An AI agent can only do what your tools allow. We design the tools, wire them to your identity provider, scope what each caller may read and change, and test the server with the MCP clients your users actually run.
DIRECT ANSWER
MCP server development exposes your product or internal tools to AI agents through the Model Context Protocol. This engagement covers tool design, authorization, permission scoping, versioning and tests with real MCP clients, delivered as code in your repository.
Best for
- SaaS teams whose customers want to use the product from Claude, ChatGPT, Cursor or their own agents
- Companies that want internal agents to act on internal systems with bounded permissions
Consider another approach
- Syncing records between two business systems without an agent in the loop
- An independent abuse and permission test of an MCP server that already exists
An agent interface, not another integration
Design tools around outcomes the agent can verify
Read and write separated
Read-only tools stay separate from tools that change data, spend money or contact people. Destructive actions need confirmation or a narrower scope.
Schemas and errors
Typed inputs, bounded result sizes and errors that tell the agent what to change, not a stack trace.
Explicit application state
Baskets, approvals and long-running jobs get their own IDs and storage, so any server instance can handle the next request.
Discovery metadata
A server card and tool annotations so clients and reviewers can see what the server offers before they connect.
Authorization through your identity provider, scoped per caller
Versioning that survives protocol and product changes
Design, build and test with real clients
Tool and access design
The list of tools, their inputs and outputs, required scopes, tenancy model and the actions that stay out of reach.Implementation and client tests
The server in your repository, automated tests and recorded runs with the MCP clients agreed in scope.Continued development
New tools, protocol updates and client changes, agreed separately. This does not create 24/7 coverage or an uptime SLA.
We run our own MCP server in production
Adjacent engineering work
We have no published client MCP server case yet, and we do not claim one. Aniron documents adjacent work: Wavect was the main contributor to the developer portal of an AI inference API, covering API keys, prepaid credits, usage visibility and integrations. Our own production MCP endpoint is described above. Neither is a promise of the same result for another system.
These are selected projects, not our full portfolio. We have shipped 100+ products since 2018.
Questions before you start
Scope your MCP server
Describe the product or internal system, the actions an agent should perform and who will connect. A short, non-sensitive outline is enough for the first conversation.