Connect AI to every tool in your stack

We build custom MCP servers that give AI agents secure, real-time access to your APIs, databases, and internal tools. One open protocol, any model, any tool. First server live in 2–4 weeks.

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How we de-risk this: free architecture review → paid discovery sprint (half up front, half on spec delivery - you own the spec) → then the full build.

The AI stack we build on

OpenAILangChainAWSn8nHugging Face

97M+

MCP package downloads/month

10K+

Community MCP servers available

1

Protocol to connect every tool

2-4 wk

First server live

Why Businesses Choose MCP Integrations

Standardised AI-Tool Communication

MCP replaces fragile, one-off integrations with a single open protocol. Build one MCP server per tool and every compatible AI client - Claude, Cursor, Windsurf, custom agents - can use it immediately. No more maintaining separate connectors for each model or framework.

Any Model, Any Tool

MCP is model-agnostic and tool-agnostic. Whether you run Claude, GPT, Gemini, or open-source models, and whether your tools are Salesforce, PostgreSQL, Jira, or a proprietary internal API - MCP provides the universal bridge. Swap models without rewriting integrations.

Real-Time Tool Use

MCP servers give AI agents live, two-way access to your systems. Agents can query databases, create tickets, update CRM records, trigger deployments, and pull fresh data mid-conversation. No stale exports or batch syncs - your AI works with the same live data your team does.

Secure by Design

MCP servers run inside your own infrastructure, so sensitive data never leaves your environment. The protocol supports granular permission scoping, transport-level authentication, and audit logging of every tool call. Role-based access controls ensure AI agents only reach what they are authorised to use.

Composable Agent Architecture

MCP servers are composable building blocks. Connect your CRM, database, project tracker, and communication tools as separate servers, then let AI agents orchestrate across all of them in a single workflow. Pair with our workflow automation services to build fully autonomous multi-step agent pipelines.

Future-Proof Investment

MCP is backed by Anthropic and adopted by major platforms including Block, Apollo, Replit, and Sourcegraph. As the ecosystem grows, every MCP server you build today becomes more valuable - instantly compatible with new AI clients, tools, and capabilities as they emerge.

Get a free architecture review - we will map your tools and show you which MCP servers would unlock the most value.

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How We Build Your MCP Servers

  1. 1

    Tool & API Audit

    We map every tool, database, and API in your stack - CRMs, project trackers, internal services, cloud infrastructure - and identify which systems would deliver the most value as MCP servers. You get a prioritised integration roadmap with estimated timelines.

  2. 2

    Server Architecture & Design

    We design the MCP server schema for each integration - defining tools, resources, and prompts that AI agents will use. Authentication flows, permission scoping, and error handling are planned upfront. You review and approve the specification before any code is written.

  3. 3

    Build & Test

    Each MCP server is built using the official SDKs with full TypeScript type safety. We test every tool call against your live systems in a sandboxed environment, validating input handling, error responses, and edge cases. Automated test suites ensure reliability across AI client implementations.

  4. 4

    Deploy & Iterate

    MCP servers are deployed into your infrastructure - on-premises, cloud, or hybrid. We connect them to your AI clients (Claude Desktop, custom agents, IDE integrations) and validate end-to-end workflows. Post-launch, we monitor usage analytics, add new tools as needs evolve, and keep servers aligned with upstream API changes.

MCP Integration vs Custom API Integration

FeatureMCP IntegrationCustom API Integration
ProtocolOpen standard, one interface for all toolsBespoke code per tool per model
Model compatibilityAny MCP-compatible client works instantlyTied to one model or framework
Adding new toolsDeploy a new server, all agents see itRewrite integration layer for each agent
Security modelBuilt-in auth, scoping, and audit loggingCustom security per integration
MaintenanceUpdate one server, all clients benefitUpdate every point-to-point connector
EcosystemGrowing library of community serversBuild everything from scratch

MCP Integration Use Cases

CRM & Sales Intelligence

An MCP server for your CRM lets AI agents pull contact histories, update deal stages, log call notes, and surface pipeline insights - all mid-conversation. Sales reps ask their AI assistant about a prospect and get live data from Salesforce or HubSpot without switching tabs or writing queries.

DevOps & Infrastructure

Connect CI/CD pipelines, cloud consoles, and monitoring tools via MCP so AI agents can check deployment status, read logs, trigger rollbacks, and query infrastructure metrics. Pair with our AI chatbots to build an on-call assistant that diagnoses incidents using live system data.

Project Management & Ticketing

MCP servers for Jira, Linear, Asana, or GitHub Issues let AI agents create tickets, update statuses, assign work, and summarise sprint progress. Team leads ask their AI assistant for a standup summary and get real-time data pulled directly from the project tracker.

Database & Analytics

Give AI agents read (and optionally write) access to PostgreSQL, MongoDB, BigQuery, or any database through an MCP server. Business users ask questions in plain English and the AI writes and executes the query, returning formatted results - no SQL skills required.

Document & Knowledge Systems

Connect Notion, Confluence, SharePoint, or Google Drive as MCP resources so AI agents can search, read, and reference your documentation in real time. Every answer is grounded in your actual content with traceable sources.

Internal Tooling & Custom APIs

Every company has proprietary internal tools with unique APIs. We build bespoke MCP servers that expose your custom systems to AI agents - inventory management, billing engines, approval workflows, or legacy systems - turning any internal tool into an AI-accessible capability.

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Frequently Asked Questions

Let us map your stack to MCP

In a free 30-minute architecture review we will audit your tools, APIs, and databases and show you exactly which MCP servers would give your AI agents the biggest impact.

  • Free demo on your real data - no commitment
  • Paid discovery phase - half up front, half on spec delivery. You own the spec.
  • Only then do we commit to the full build
Book your free demoOr send a brief →