MCP SERVER DEVELOPMENT

MCP Server Development Company
Connect your product to AI assistants.

We design, build and secure Model Context Protocol (MCP) servers that let Claude, ChatGPT, Cursor and your own AI agents use your product and internal systems safely. We built and run the Feedlio MCP server in production, listed on the official MCP Registry.

Book a call →See the Feedlio MCP server
MCP IN PRODUCTIONFEEDLIO · LIVE
feedlio_mcp_tools8// read and write tools
mcp_directories3// Official MCP Registry · Smithery · mcpservers.org
ai_clientsClaude · ChatGPT// tested with both
networks_via_mcp12// social networks live
transportStreamable HTTP// OAuth 2.1 sign-in
spec_revision2026-07-28// current MCP specification

WHAT WE BUILD

MCP servers that hold up in production.

Remote MCP servers for SaaS

Multi-tenant servers over Streamable HTTP that let your customers use your product from Claude, ChatGPT and other assistants.

Internal MCP servers

Connect CRM, ERP, ticketing, databases and documents to your company’s assistants and agents, with per-user permissions.

OAuth 2.1 authorization

Protected Resource Metadata, audience validation, scopes and step-up, done to the MCP specification. No token passthrough.

Tool design and schemas

Tools built around user intent, with schemas, descriptions and errors the model can follow, and idempotent writes.

Security and approvals

Defences against prompt injection and tool poisoning, least-privilege scopes, rate limits, audit logs and human approval for side effects.

Testing and evaluation

MCP Inspector, contract tests and model-in-the-loop evaluations, so the right tool is chosen for each real request.

Registry publishing and docs

Official MCP Registry listing under a verified namespace, directory submissions and setup guides for each client.

Upgrades and migrations

Move 2025-era servers to the stateless 2026-07-28 revision and v2 SDKs, with backward compatibility for older clients.

USE CASES

Where MCP pays off.

MCP is worth building when more than one AI client or agent needs the same system.

01

SaaS products

Let customers run your product from their AI assistant, and get a new distribution channel through MCP directories.

02

Knowledge and documents

Search policies, contracts and tickets with results that respect each user’s permissions.

03

Customer support and CRM

Look up orders and accounts, draft refunds and log activities, with approval for anything that changes data.

04

Engineering and operations

Query logs, check deployments and open incidents, with narrow credentials and a small blast radius.

CASE STUDY

Proof, not promises.

CASE STUDY · PUBLIC MCP SERVER

Feedlio MCP server

Our hosted MCP server lets Claude, ChatGPT and other AI assistants schedule, list, reschedule and cancel social posts and manage media across Feedlio workspaces. Users sign in on Feedlio’s own page, so their credentials never pass through the chat, and a person reviews each post before it goes live.

12
Networks live
3
MCP directories listed
Daily
Used for our own marketing
View Full Case Study →

PROCESS

From idea to listed server.

A production internal server typically takes 4 to 8 weeks; a public multi-tenant SaaS server 8 to 14 weeks.

01

Map real requests

Write the 5 to 10 things users will ask, and decide local, remote or both.

WK 1
02

Design tools

One tool per intent, reads separated from writes, schemas and error messages for the model.

WK 1–2
03

Build and authorize

Server on the v2 SDKs, OAuth 2.1, tenant isolation, idempotent writes and approvals.

WK 2–6
04

Test and secure

Inspector and contract tests, model evaluations and prompt-injection tests.

WK 6–8
05

Publish and launch

Deploy, publish to the MCP Registry and directories, and document setup for each client.

WK 8+

SCOPE

Pick the scope you need.

Planning estimates from our delivery experience, assuming a reasonably documented API. You get a fixed quote after discovery.

01 — Prototype1–2 wks

Internal prototype

3 to 5 read-only tools

Prove the idea with a private server your team can try in Claude or Cursor.

  • stdio or private HTTP
  • MCP Inspector testing
  • Tool and schema design
Book a call →
02 — Production4–8 wks

Internal production server

8 to 15 tools including writes

A server your company can rely on, connected to your identity provider.

  • SSO-based OAuth
  • Approvals and audit logs
  • CI tests and evaluations
Book a call →
03 — Public8–14 wks

Public SaaS MCP server

Multi-tenant, listed

Like Feedlio: your customers connect their own assistants to your product.

  • Multi-tenant OAuth and scopes
  • Rate limits and observability
  • Registry listing and setup docs
Book a call →

FAQ

MCP server questions.

An MCP server exposes your system’s tools and data through the Model Context Protocol, an open standard for connecting AI applications to external systems. Any MCP-compatible client, such as Claude, ChatGPT, Cursor or your own agent, can then discover and use those tools.
No. Anthropic created MCP, but it is now an open protocol under the Linux Foundation’s Agentic AI Foundation, with adoption across ChatGPT, Cursor, Gemini, Microsoft Copilot and Visual Studio Code. Feedlio’s MCP server works with both Claude and ChatGPT.
No. An MCP server usually sits on top of your existing API and makes it usable by AI assistants, adding intent-based tools, clear descriptions, readable errors and approval steps.
An internal prototype takes 1 to 2 weeks, a production internal server 4 to 8 weeks, and a public multi-tenant SaaS server 8 to 14 weeks. Timelines depend on tool count, the authorization model and the state of your API.
With layers: minimal scopes, per-user tool lists, server-side validation, rate limits, audit logs, and human approval for actions with external side effects, ideally enforced inside your product so it works with any client.
For any remote server that touches user data or takes actions, yes. Your server acts as an OAuth 2.1 resource server, publishes Protected Resource Metadata and accepts only tokens issued for it. Local stdio servers use environment credentials instead.
Yes. We publish public servers to the official MCP Registry under a namespace you own, submit them to directories your users browse, and write the setup guides. The Feedlio server is listed on the MCP Registry, Smithery and mcpservers.org.

START YOUR MCP PROJECT

Put your product inside AI assistants.

Tell us which system you want to connect and who will use it. We will scope the tools, the authorization model and a realistic timeline.

No commitment — a technical deep dive with our lead engineers · Trusted by 65+ teams since 2016

Book a call →