MCP + API Engineering
Custom MCP servers, API sprints, and workflow packs.
Your AI agent can reason about your tools. We make it able to use them. Fixed-price builds, code you own, no lock-in.
45 minutes to map what you're connecting. Written spec and fixed quote within 48 hours, engineer-authored.
Your team works in Claude or GPT every day. But anything that touches an external API is still manual: pull the ID, open the dashboard, paste the payload, wait, check back.
The APIs are fine. The glue is missing.
We build the glue properly - auth, safe scopes, retries, logging, tests - then hand you the repo.
One boundary, stated plainly: we wire platforms into stacks. We do not do model fine-tuning, prompt-engineering retainers, or AI strategy decks.
Services
What's in an integration sprint.
Custom MCP servers
Give your AI agent direct access to your internal tools - Salesforce, Jira, Notion, or any REST API. We build the MCP server: auth handling, tool definitions with safe scopes, error surfaces the agent can act on, and a test suite. The agent calls the tool. You watch the log.
API integration sprints
3-5 day fixed-price sprints to wire two systems together. Scoped upfront, priced upfront, shipped fast. Retry with backoff and failure alerting built into every webhook handler - silent failures are not a deliverable.
Workflow packs
n8n or Make automations designed for production use: proper error handling, retry logic, monitoring hooks, and a runbook so your team can operate it without us. Not a demo workflow - a production one.
Every engagement ships the same standard
- Working MCP server or integration (Node or Python), built for production
- Auth handling, safe tool scopes, error surfaces, retry logic
- Test suite that runs in your CI - not a screenshot of green checkmarks
- Architecture diagram, deployment guide, runbook, credential inventory
- GitHub repo transferred to you - full source, full history
- 60-minute recorded handover session with your team
- 30-day post-launch fix window - defects in delivered scope fixed free
You own everything. No lock-in by design.
Audience
Who this is for.
Technical teams
- CTO, head of engineering, or founder-engineer
- Your team already uses Claude or GPT daily
- You have internal APIs that should be agent-callable but aren't
- You want code you own, not a SaaS wrapper you pay forever
Platform DevRel
- API adoption is blocked on missing integration examples
- Partner directory is thin and the docs backlog isn't shrinking
- You want production-grade starters published under your GitHub org
- Co-marketing welcome, not required
Indie hackers shipping AI products
- Building something that needs agents to call external services
- Want the integration layer done right so you can ship the product
- Fixed price is non-negotiable - hourly meters kill runway
- One repo, full source, your license
Pricing
Scoped per project.
Always fixed, never hourly.
One number, agreed before work starts. No hourly meter, no scope-creep invoices. The scope call produces a written spec - you decide from the spec, not a pitch.
Working Pipeline Guarantee
Written acceptance criteria before we build. It works, or we keep working at no additional cost. If we can't meet the criteria, the final milestone is waived and you keep everything built, plus all documentation.
Schedule a scope callFull guarantee detail on /pricing
FAQ
Questions
What's an MCP server and why does my team need one?
MCP (Model Context Protocol) is the standard that lets Claude, GPT, and other AI agents call external tools directly. Without one, your agent can reason about your Jira tickets, Salesforce records, or internal APIs - but it can't touch them. You copy-paste IDs between tabs. An MCP server closes that gap: the agent calls the tool, within scopes you define, with every call logged. One build. Permanent workflow change.
Isn't this too early-stage to build on in production?
The protocol itself is the thin layer. The durable asset underneath it is the integration logic: auth, API handling, scoping, retry, business rules. That logic ports if the protocol ever changes, and we build the separation deliberately. Anthropic, OpenAI, and major platforms are promoting MCP as their first-class path. The risk of waiting is higher than the risk of building.
Couldn't our own engineers build this?
Yes. It's a bandwidth trade, not a capability gap. The OAuth edge cases, rate-limit behavior, and undocumented API failures take time to discover and document. A fixed-price sprint - $1,500 to $4,000 depending on scope - typically costs less than two engineer-weeks of distraction, and your team owns and extends everything afterward. Check the scope call first and decide from the written estimate.
What does the sprint actually deliver - can I see the code?
Yes. Our own workflow packs and starter servers are on GitHub - public code is the fastest way to verify us. Client work ships in your repo under your license. The sprint deliverable is: working integration, CI-runnable test suite, architecture diagram, deployment guide, runbook, and a recorded handover call. Source, history, and docs transferred to you on the final milestone.
Start with a scope call.
45 minutes to map what you're connecting and why. You get a written spec and a fixed quote within 48 hours, engineer-authored. If an existing tool or open-source starter covers your case, the spec says that instead.
Schedule a scope call