Ship It Live — $1,999 flat
Design + build + deploy · kickoff in 24h · limited slots
Ship It Live · MCP sprint
Your product, usable by AI assistants, in 14 days.
The integration surface your customers will expect within a year. Built properly, with tools an assistant can actually use without guessing.
Quick answer
A Model Context Protocol server exposing your product to Claude and other AI clients can be designed, built and deployed in 14 days for a fixed $1,999. That covers tool and resource design, authentication, error handling, documentation and deployment. Well-designed tools matter more than the number of them.
The plan
Day one to day 14, written down.
You get this schedule before you commit, not after. If a phase slips, that is mine to absorb — the price and the date were agreed before anything started.
- 1
Days 1–2
Tool design
Which operations to expose and how to describe them. This is the whole job — a badly named tool with a vague description is one an assistant will misuse confidently.
- 2
Days 3–6
Build the core
Tools, schemas, validation and error paths. Errors are written to tell a model what to do differently, not just that something failed.
- 3
Days 7–10
Auth and hardening
Authentication, scoping and rate limits. An MCP server is an API surface with an unusually creative client, so the limits matter.
- 4
Days 11–13
Test with real clients
Driven from an actual assistant against real tasks. Tools that read well on paper often fail the moment a model has to choose between them.
- 5
Day 14
Ship
Deployed, documented, with install instructions and a short handover on adding tools yourself.
What $1,999 gets you
Everything needed to launch — nothing padding the invoice.
Who books this
Built for
SaaS products whose customers already ask about AI integration
API-first companies who want to be reachable from inside assistants
Internal platform teams giving their own agents safe access to systems
Real situations
Five ways this shows up, and what actually fixes it.
Not hypothetical — the shape of the problem before someone books this sprint, and the specific part of the build that resolves it.
Situation 1
Customers already asking about AI integration
A SaaS product's customers have started asking whether it works with Claude or other AI assistants, and there's currently no answer beyond 'not yet.'
A production MCP server exposes the product's real capabilities to AI clients in 14 days, with tool design as the actual focus of the work.
Situation 2
An API that's technically documented, practically hard for a model to use
A product has a full API, but its structure and naming were designed for human developers reading documentation, not for a model choosing between tools.
Tool and resource design — the part that decides whether an assistant uses it correctly — is the whole job, not an afterthought bolted onto the existing API.
Situation 3
Considering wrapping the entire API as MCP tools
A team's instinct is to expose every existing API endpoint as its own MCP tool, assuming more tools means more capability for the assistant.
Fewer, well-named tools that map to real user intentions outperform an exhaustive mirror of the API — models choose badly from long menus.
Situation 4
Worried about letting an AI call production endpoints
A team is interested in MCP but concerned about the risk of an AI client triggering a destructive action like a delete or a refund by mistake.
Destructive operations are gated behind confirmation or excluded entirely, so a misreading assistant can't cause irreversible damage.
Situation 5
An internal platform team building safe agent access
A platform team wants their own internal agents to access company systems safely, but has no standardized, scoped way to expose those systems yet.
Authentication, scoping and rate limiting are built into the server, giving internal agents a properly bounded interface rather than raw access.
The honest part
When 14 days is the wrong answer.
A fixed deadline only works when the scope genuinely fits inside it. These are the cases where I will tell you so rather than take the booking.
Exposing destructive operations without confirmation. Delete, refund and send are gated or excluded — an assistant misreading a request should not be able to be catastrophic.
Wrapping an entire API surface tool-for-tool. Fifty tools is worse than eight; models choose badly from long lists, and I will argue for the shorter one.
Products with no API and no data model yet. That is the project to do first, and this sits on top of it.
Inside the 14 days
- Tool design — the part that decides whether an assistant uses it correctly
- Resources and prompts where they fit the protocol better than tools do
- Authentication, including OAuth where your product needs it
- Input validation and error messages written for a model to recover from
- Rate limiting and scoping, so a confused agent cannot cause damage
- Documentation and install instructions your users can follow unaided
- Deployed and running, local and remote transport as appropriate
- Source code and configuration yours at handover
Quoted as one number before day one. A week running long is mine to absorb.
Outside the line
- Exposing destructive operations without confirmation. Delete, refund and send are gated or excluded — an assistant misreading a request should not be able to be catastrophic.
- Wrapping an entire API surface tool-for-tool. Fifty tools is worse than eight; models choose badly from long lists, and I will argue for the shorter one.
- Products with no API and no data model yet. That is the project to do first, and this sits on top of it.
Real work, sized and priced separately. You hear it before you book, not at handover.
Questions
Before you book
A standard way to expose your product's capabilities to AI assistants, so a model can use your tools directly instead of a user copying data between windows. The Model Context Protocol is the interface, and a server is your side of it.
Tools map to intentions, not endpoints
A 14-day MCP sprint ships a server assistants can choose tools from, not a mirror of every API route. Fixed price: $1,999.
| In scope | Out of scope |
|---|---|
| Tools named for intentions | One tool per REST endpoint |
| Useful resources and context | Expose the whole OpenAPI surface |
| Readable auth, errors, and docs | Unbounded admin power |
| Destructive operations gated | Delete, refund, or wipe with no confirm |
Design and handoff bar
- Intention map is written before routes
- Clients authenticate before calls
- Destructive tools need confirmation or stay out
- Bad inputs return readable errors
- Deploy docs work for a second engineer
Soft planning rule (not an SLA): lock the primary job early, review edge cases before launch week, and keep accounts and source in your name at handoff.
Extra questions
Can we wrap every endpoint?
Which clients work?
Is day 14 a guarantee of correct tool choice?
Other sprints
14 days from now, this could be live.
A 30-minute call decides whether the scope fits. If it doesn't, I'll tell you what would.