MCP Servers
Custom Model Context Protocol servers that expose your systems to Claude, ChatGPT, Cursor, and any MCP-aware client.
Standardized tools and data for any agent
MCP is becoming the common interface between AI clients and your tools and data. We design, build, and deploy MCP servers that make your internal APIs, databases, and workflows usable from any MCP-aware agent — with auth, scoping, and audit baked in.
Outcomes
Our approach.
Surface design
Decide what to expose: resources (read), tools (write), prompts (templates). Scoped to the right audience — internal, partner, or public.
Auth & isolation
OAuth, SSO, or scoped tokens. Per-user, per-tenant scoping. Rate limits and quotas so one client can't take the server down for everyone.
Deploy remote or local
Local stdio for Claude Desktop power users. Remote HTTP/SSE for teams and partners — on Lambda, Azure Functions, or Cloudflare Workers.
Version & observe
Every tool call is traced. Versioning contracts means clients don't break when you ship. Compatibility guarantees are explicit.
What you get.
Production-shaped, from day one.
import { Server } from "@modelcontextprotocol/sdk/server"
const server = new Server({ name: "crm", version: "1.0.0" })
server.tool("search_accounts", {
input: { query: "string", limit: "number?" },
handler: async ({ query, limit = 10 }, ctx) => {
ctx.requireScope("crm:read")
const accounts = await crm.search(query, { limit })
return { content: accounts }
},
})
server.tool("update_account", {
input: { id: "string", fields: "object" },
requiresApproval: true,
handler: async ({ id, fields }, ctx) => {
ctx.requireScope("crm:write")
return crm.update(id, fields)
},
})A proven shape for this solution.
We adapt it to your cloud, data, and compliance requirements. Nothing here is boilerplate — every layer is justified by the numbers.
Where this shows up.
- Internal data lookup tools for Claude Desktop users
- Remote MCP servers exposing CRM, ticketing, and warehouse
- Vendor-facing MCP server for partner integrations
- Dev-tooling MCP servers for code, logs, and runbooks
What we use.
We’re not religious about tools. We pick what fits your constraints and team.
What teams usually ask.
Why MCP instead of just building a REST API?
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MCP is how agent clients (Claude Desktop, Cursor, custom agents) expect to discover and use tools. It gives you one standardized surface that works across clients and gets better as the ecosystem grows.
Is MCP ready for production?
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For internal and partner use cases — yes, today. The spec is stabilizing quickly. We version contracts explicitly so upgrades don't break clients.
Can MCP servers be secured for multi-tenant use?
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Yes — OAuth/SSO at the gateway, per-user scoping in the server, rate limits and quotas per tenant, and full audit logs on every tool call.
Related solutions.
Agents & Workflow Automation
Agentic workflows that read, write, and act across your existing tools — with human-in-the-loop where it matters.
Cloud AI Infrastructure
We stand up the platform layer so your AI systems are secure, observable, scalable, and cost-governed from day one.
Conversational AI & Chat Lookup
Production-grade chat systems that answer from your sources with citations, guardrails, and session memory.
Ready to accelerate your tech growth?
Schedule your free consultation today and let's discuss how we can help your business scale efficiently.
