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mcp integration development

Model Context Protocol integrations, built and deployed by Gaper.

Gaper builds the Model Context Protocol layer that connects your agents to your systems: MCP servers, tools, and clients wired to your data, APIs, and auth. We deploy it in your stack and hand it over.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · agent runtime
$ gaper deploy agent --to production
✓ plan ……………… 4 steps
✓ retrieve …… 1,240 docs grounded
✓ tool ………… salesforce.update_record
✓ eval ………… 12/12 checks passed
● live · p95 1.2s · 0 errors
● in productionowned by your team
In one sentence

Model Context Protocol integration is the connective layer that lets AI agents discover and use your systems through a standard interface. Gaper builds the MCP servers, tools, and clients that expose your data, APIs, and actions to agents securely, then deploys them in your stack with auth, scopes, and audit trails.

ProductionNot another demo
Model-agnostic
In your cloudYour auth, your data
You own itCode, evals, runbook
Why this matters

An agent is only as useful as the systems it can reach. Most MCP work stalls at a local demo: a server that lists tools but never safely touches production data, auth, or write-backs.

Production filter
  • Does it touch real systems?
  • Can the outcome be measured?
  • Where does human approval stay?
  • Who owns it after launch?
Free AI assessment

Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.

Map your first production agent
How we work

From strategy to production, owned by your team.

  1. 01

    Map the workflow

    We start from the documents, SOPs, portals, inboxes, and spreadsheets your team already uses, then turn the repeatable path into an agent workflow map.

  2. 02

    Build the supervised agent

    We build on OpenAI, Claude, Gemini, or the right model for the job, with evals, guardrails, citations, and human approval gates where risk matters.

  3. 03

    Connect the stack

    The agent gets the data layer, APIs, MCP tools, auth, and write-backs it needs to finish work inside your systems, not beside them.

  4. 04

    Sandbox, verify, go live

    We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.

What we build

Agents wired into the systems you already run.

MCP servers over your systems

Servers that expose your databases, APIs, SaaS tools, and internal services to agents through one standard protocol, scoped to exactly what each agent should reach.

Tools, resources, and prompts

Typed tools for actions, resources for grounded context, and reusable prompts, all defined so agents call them reliably and predictably.

Auth, scopes, and secrets

OAuth, API keys, and per-tool scopes wired in so the agent acts as the right identity and never sees more than it should.

MCP clients in your agents

We connect your agents on OpenAI, Claude, or Gemini to your MCP servers, so they discover tools at runtime instead of being hardcoded.

Write-backs and side effects

Tools that update the CRM, file the ticket, or post the record, with human approval gates on the steps that carry real risk.

Evals, logging, and rollback

Every tool call is traced, evaluated, and reversible, so you can see what the agent did, prove it, and roll it back.

Deployed in your stack, not a public connector

Your MCP servers run where your data lives: your cloud, your auth, your controls. The agent reaches your systems through scoped tools, so integration does not widen your attack surface.

  • Runs in your environment or ours
  • Per-tool scopes, SSO, and audit logging
  • No data leaves your boundary
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the servers and the code

We build the MCP layer alongside your team and hand over a documented codebase. No black box, no proprietary middleware, just standard MCP servers and clients you can extend and run without us.

  • Clean, documented MCP servers and tools
  • Knowledge transfer built into delivery
  • Standard protocol, no lock-in
Handover state
handoff packageCode, runbook, evals, dashboard
owned by your team
Source repoRunbookEval suiteOwner training

Access your auth

Data your environment

Ops monitor or handoff

Safe to run against production

The gap most MCP work never crosses is touching real systems safely. We gate risky tool calls behind approvals, eval every action before launch, and give every write-back a rollback path and an owner.

  • Approval gates on consequential actions
  • Evals that pass before any tool goes live
  • Traces and rollback on every call
Release gate
  1. 01Eval suiteknown + edge casespass
  2. 02Policy checkguardrails enforcedpass
  3. 03Human fallbacklow-confidence routedhold
  4. 04Releaseshipped to prodlive

p95 latency 1.2s

eval pass 12/12

rollback ready

Model and stack agnostic
OpenAIClaudeGeminiLangChainMCPPythonTypeScriptPinecone
FAQ

Questions buyers ask us.

What is a Model Context Protocol integration?+
Model Context Protocol is an open standard that lets AI agents discover and use external systems through a common interface. An MCP integration is the server, tools, and client that expose your data and actions to an agent. Gaper builds and deploys that layer into your stack.
Does Gaper staff out or place MCP developers?+
No. We do not hire out, place, or supply developers. Gaper builds and deploys the MCP integration as a system you own. We deliver the servers, tools, evals, and runbook, and hand the code over to your team.
Do we own the MCP servers you build?+
Yes. We build and deploy the integration, then hand over the full codebase, evals, and runbook. The servers use the standard protocol with no proprietary lock-in, so your team can run and extend them on its own.
Which models and systems do you connect?+
We are model-agnostic: agents on OpenAI, Claude, or Gemini, connected via MCP to your databases, APIs, and SaaS tools like Salesforce, Zendesk, Postgres, and Snowflake, deployed in your cloud with your auth.
See what operators from other companies think about AI Agents:
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Ready to deploy your first agent?

Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.

Build, deploy, runYour cloudYou own the code