MCP Server Development Services

MCP server development for tools an AI client can use without broad access.

We build Model Context Protocol servers that expose a small, typed set of business tools or resources to compatible AI clients. A focused release covers one client, one underlying system, delegated identity or a bounded service account, read-first tools, confirmation for writes, audit records, failure handling, and compatibility tests.

Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.

Evidence and scope

Starts at $20K

Focused first release

One supported AI client, one business system, a bounded tool set, identity, audit, and recovery.

8 to 12 weeks

Typical focused timeline

Tool-contract design, security proof, build, adversarial testing, client acceptance, and handover.

One client

Deliberate boundary

A protocol and policy layer; not the agent, model, business API, or workflow owner.

Evidence · planning contextSee the work

The brief

Start with what is not working.

Good software decisions begin with the constraint, not a list of features or a preferred technology.

01

Does the assistant need live business data, yet the only proposed credential can read or change far more than the task requires?

02

Can operators see which user, client, model session, tool, arguments, approval, result, and downstream record belong to each call?

Plain answer

MCP server development exposes selected business tools and resources to a compatible AI client through Model Context Protocol. RaftLabs builds bounded servers with typed schemas, delegated identity, least privilege, write confirmation, audit, and failure handling. A focused release starts at $20,000 and usually takes 8 to 12 weeks.

The demo could update a customer. It could also update every customer.

The first tool accepted a record ID and free text, then used one service credential with broad write access. The assistant completed the happy path. Nobody had tested cross-tenant IDs, duplicate retries, hostile text returned by the CRM, or the record needed to explain a disputed change.

Focused delivery baseline

$20K
starting first release
One client and one underlying system
8-12 weeks
typical focused timeline
Includes adversarial and compatibility tests
Read first
initial capability bias
Writes added only with explicit controls

RaftLabs does not currently publish a named MCP-server outcome case. These figures describe a bounded delivery plan, not guaranteed client compatibility or task completion. Acceptance should measure schema-valid calls, denied access, redaction, pagination, latency, rate limits, duplicate retries, write reconciliation, audit completeness, injected content, client behaviour, and recovery from downstream failure.

Build a custom MCP server when a compatible AI client needs controlled access to proprietary systems.

Start with one client, one system, and a few valuable tools. A connector or direct API call is usually better when the capability is common and fixed.

A fit
01

The assistant or agent must read or change proprietary records through a supported MCP client.

02

Identity, tenancy, least privilege, sensitive fields, write approval, audit, or failure handling is material.

03

Business-system, security, AI-platform, and operational owners can approve tool contracts and test cases.

Not a fit
01

The need is only drafting, summarisation, search, or chat without access to a business system.

02

A supported connector already provides the required scope, identity, controls, and service level.

03

The underlying API, record ownership, user identity, approval policy, or security owner remains unresolved.

Separate the protocol layer from the AI system

NeedBest fitBoundary
Expose selected tools to compatible AI clientsMCP serverTool schema, client support, identity, access, confirmation, audit, and errors
Provide a deterministic interface to business logicAPI developmentEndpoints, contracts, authentication, versioning, reliability, and consumers
Plan and complete a goal with toolsAI agent developmentModel, state, decisions, tool selection, human gates, and outcome
Coordinate several model or tool stepsAI orchestrationSequence, routing, state, retries, fallbacks, and review
Add model features to an existing productLLM integrationUse case, provider, prompts, context, evaluation, and operation

Scope

What belongs in a focused MCP server

  • 01
    Typed tool and resource contracts
    Give each capability one narrow job, explicit inputs, bounded output, clear descriptions, stable identifiers, pagination, errors, and examples that match the underlying business API.
  • 02
    Identity and least privilege
    Authenticate the client, preserve the end-user or service identity, enforce tenant and row scope, separate roles, minimise credentials, and deny unapproved fields or operations.
  • 03
    Write confirmation and idempotency
    Preview material changes, require the agreed approval signal, cap batch size, control duplicate retries, preserve downstream identifiers, and reconcile the final business record.
  • 04
    Untrusted-content and output controls
    Treat tool results and resource content as data rather than instructions. Filter sensitive fields, bound result size, validate output, and keep injected text away from policy decisions.
  • 05
    Observability and client compatibility
    Trace calls, identities, arguments, approvals, timing, results, errors, and side effects. Test the named clients and protocol features, then record supported versions and known gaps.

How it works

From business capability to accepted MCP tool contract

  1. Phase 1
    01

    Define client, system, identity, and tools

    Choose the supported client, underlying system, user roles, read and write jobs, resource boundary, owners, approvals, measures, limits, and acceptance examples.

  2. Phase 2
    02

    Prove access and threat boundaries

    Verify APIs, schemas, credentials, delegated identity, tenancy, sensitive fields, untrusted content, rate limits, errors, client behaviour, and downstream side effects.

  3. Phase 3
    03

    Build the bounded MCP server

    Create typed tools or resources, validation, least privilege, confirmation, idempotency, redaction, pagination, audit, tracing, recovery, and compatibility tests.

  4. Phase 4
    04

    Test clients and hand over

    Run accepted and adversarial calls, reconcile writes, rehearse denial and outages, document version support, train owners, and release after security approval.

Risk

What the MCP specification must settle

Client and version support
Name transports, features, authentication, approval behaviour, deployment, and versions in scope. Retest compatibility when the client or protocol changes.
Delegated authority
Decide whether the server acts as the user or a service, how tenant and record access is enforced, and which system remains authoritative for permission.
Prompt injection through data
Treat content returned by tools or resources as untrusted. Keep it from redefining tool policy, expanding access, or bypassing write approval.
Side effects and retries
Define preview, approval, idempotency, batch limits, timeouts, partial success, rollback, reconciliation, and the person who resolves a disputed write.

Scope and price

A focused MCP server starts at $20,000.

Begin with one supported client, one system, a bounded tool set, explicit identity, read-first access, audit, compatibility tests, and an operating owner.

A broader MCP estate commonly reaches $35,000 to $80,000. Use an existing connector when its access, tools, compatibility, and support already fit.

Starting investment

Starts at $20,000

A focused release usually takes 8 to 12 weeks. Several clients, systems, tenants, write paths, legacy APIs, or formal security reviews extend the plan.

A protocol does not grant authority

Every tool still passes through the approved identity, permission, policy, and downstream business controls for the operation.

Compatibility is named and tested

The release record lists supported clients, protocol features, transports, authentication, versions, test results, and known gaps.

Related AI integration services

MCP server development questions

An MCP server exposes selected tools, resources, or other supported capabilities to a compatible AI client through Model Context Protocol. The server sits between the client and underlying systems. It should validate inputs, enforce identity and access, control outputs and side effects, record calls, and handle failures.

An API is the deterministic business interface the MCP server often calls. The MCP server describes selected capabilities in a form compatible AI clients can discover and invoke. An agent decides when to use tools and may coordinate several steps. MCP does not replace the API, model, workflow policy, or agent runtime.

Not automatically. Clients can differ in supported protocol features, transports, authentication, user interface, approval behaviour, limits, and release cadence. We name the client versions and capabilities in scope, test them directly, and document gaps. Compatibility with an untested future client is not a delivery guarantee.

Start with narrow inputs and permissions. Separate read from write, show a preview, require an approved confirmation for material changes, use idempotency to control retries, record before and after state where appropriate, cap volume, expose errors, and keep destructive or regulated decisions under an accountable human or system.

A focused release starts at $20,000 and usually takes 8 to 12 weeks. It covers one supported client, one underlying system, a bounded tool set, authentication, access control, confirmation, audit, failure handling, compatibility tests, deployment, and handover. Several clients, systems, tenants, write paths, or security reviews increase scope.

Work with us

Bring the business tools the AI client should and should not reach.

Share the client, user roles, underlying systems, APIs, read and write jobs, sensitive fields, approval rules, audit needs, and security owner. We will define a bounded server.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.