Your agent nails the demo. Then it has to act on a real internal tool — and the hand-rolled MCP server starts falling over. I turn that flaky integration into a production-grade server your team can trust, in a fixed-scope sprint.
The SDK wrapper is the easy part. The reason yours won't page you at 2am — fail-soft behavior, scoped auth, pinned versions — is the part I build.
“Just call the API” stopped being enough — your agent has to act on internal tools. Someone wired up an MCP server under deadline; it sails through the happy path, then a backend hiccups and takes the whole agent down with it. The hard parts are exactly the ones that got skipped.
One of your internal tools, shipped as a production-grade MCP server your team can run and trust. The scaffold is the fast start; the hardened layer on top is the deliverable — exactly what the commodity gigs leave out.
A design, not a try/except. Backend-down, rate-limit, 401/403/404, malformed input, timeout — each returns a clean structured error that tells the agent when to retry, never crashing the session.
Per-tool scoping and a trust boundary that's proven, not asserted — tested against a resource the token can see and one it can't, so you know the boundary actually holds.
trust-tier isolationTwo axes, not one: the dependency lockfile and the upstream API-version header — so a fresh install reproduces and the backend can't silently change response shape under you.
deps + API versionHermetic tests that pass on a clean checkout — covering the tool surface and the real failure set — so reliability is something you can re-verify, not take on faith.
green on clean checkoutA README a teammate can follow to run it unaided — env, install, register, run. No “works on my machine,” no single point of failure on the one laptop it was built on.
teammate-runnableOne live walkthrough, registered and running in your environment, accepted against an explicit Definition of Done — plus a 14-day support window on delivered scope.
accepted vs. DoDAnyone can wrap the SDK and pass the happy path. The hardened layer above — the boundary that holds, the failure set that's handled, the install that reproduces — is what turns a demo into something your senior engineers don't have to babysit.
The capability is public and checkable: an open-source engine with a real test suite, and a production read-only server built end-to-end against the exact delivery process below.
Watch the engine go from a YAML manifest to a live MCP serve call — the fastest way to see exactly what a sprint delivers, no checkout required.
Watch the demoA manifest-driven MCP server scaffolder and runtime hub. Write a YAML manifest, get a Claude MCP server scaffold — with batch registration and a live routing hub. The hardened production layer is built on top, per engagement.
View on GitHubRead+write over a real external API — the exact common client ask. A public GitHub REST API MCP server built against the same delivery kit: write tools off by default, typed rate-limit handling, fail-soft + version-pinned.
Read the case studyThese are my own public, tested builds — and an honest look at how I validate (and kill) systems. Every number links to the repo or write-up that backs it.
A manifest-driven MCP scaffolder + runtime. 179 passing tests, public repo, 90-second Loom demo of a live test run.
Read the case studyRead+write over a real external API — the exact common client ask. Write tools off by default, typed rate-limit handling, 74 passing tests, public repo.
Read the case studyOS-level control when there's no API: screenshot, windows, input, screen-recording. Input off by default, rate-capped, 121 passing tests, public repo.
Read the case studyRetrieval-augmented search exposed as an MCP tool. Local ONNX embeddings, fail-soft, 50 tests, $0 inference cost.
Read the case studyThe reliability story: how I forward-test systems honestly and retire the ones that don't earn their keep. Rigor, not returns.
Read the case studySigned SOW + access. A scoping questionnaire picks the one tool, the actions that matter, the auth model, and what failure should look like. Kickoff call confirms it; we write the manifest.
Scaffold via mcp-factory, then implement the handlers for your tool. (If the API is undocumented, an explicit discovery line-item maps endpoints, auth, and real response shapes first — that's the real risk axis.)
Where the value lives: auth-scoping, fail-soft across the real failure set, version-pinning on both axes, and error messages that tell the agent when to retry.
Test suite green on a clean checkout, then live hub validation in your environment — including the auth-scope boundary proven against a private resource pair.
Setup docs, a live walkthrough, and acceptance against the Definition of Done — then a 14-day support window on delivered scope.
A repeatable flow: scope → build → harden → handoff. Fixed scope, an explicit Definition of Done, and a 2-day buffer held for the inevitable auth or edge-case surprise.
The number comes after a short scoping questionnaire, never before. The ladder below is the shape; we land on the right rung once we've seen your one tool, its auth model, and whether the API is documented.
No. Work is fixed-scope sprints, scoped and quoted flat after a short call. The entry point is a $1,500 MCP Readiness Audit (written report, no code), credited toward a Sprint if you proceed within 60 days.
A typical Integration Sprint ships a working, tested server in about two weeks. Multi-source and self-hosted builds are larger and scoped separately.
The audit covers that too — a read of the existing server for auth-scoping gaps, fail-soft handling, version-pinning, and test coverage, delivered as a written risk log. The MCP spec is still moving; existing servers will need updates as it changes.
Python and Node MCP servers over REST, on cloud or self-hosted / on-prem. Auth via API-key, OAuth, or session-scoping. If your tools speak HTTP, they can be wired.
That's the whole point. mcp-factory is public with 179 passing tests, and there's a 90-second Loom demo showing the test run, auth-scoping, and fail-soft handling live.
Not yet — and I won't fabricate any. Instead I publish tested code you can check yourself and a case study on how I validate systems honestly (including killing ones that don't work). That's the trust signal, in place of borrowed logos.
Tell me the one system you'd wire in first. I'll send a short scoping questionnaire, set the tier, and you'll know exactly what you're getting before anything is signed.
No call required to start — a working repo and a clear scope beat a sales pitch.