4.9/5 on Clutch — 13 verified reviews

MCP Development Services

Most AI agents stay trapped behind brittle, one-off integrations that break whenever a single tool or vendor changes. Model Context Protocol, the open standard connecting AI models to tools and data through one consistent interface, ends that. Kodexo Labs builds those production servers.

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TRUSTED BY ENTERPRISES

Your agents need to reach the systems that actually run your business: your CRM, your databases, your internal tools. We build the MCP servers that connect them safely and monitor every tool call.

Our Core Capabilities:

  • Custom MCP servers in Python, TypeScript, or Go exposing tools.

  • Enterprise integration linking servers to Salesforce, SAP, and your databases.

  • Security and authentication with OAuth 2.1, mTLS, and scoped permissions.

  • Multi-agent architecture where several agents share one clean tool layer.

  • Legacy migration wrapping older systems in an MCP-compatible interface layer.

  • Observability and testing that track tool calls, latency, and failures.

IN THE NEWS

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MCP Development Services
51

AI-powered products

94%

Client retention rate

Top-Rated

AI development company

Since 2021

Weekly client demos

MCP Integration Services and Server Development

Every MCP setup has three parts working together: a host application, a client inside it, and the server that exposes your tools. We build and connect all three so your agents reach real business systems reliably.

Custom MCP Server Development

We build MCP servers in Python, TypeScript, or Go that expose your internal tools and data to any AI agent through one interface.

Tool exposure

Agents run your own code and tasks, with no glue or extra API layer.

Resource exposure

Agents read your own files and records live, so the data is never stale.

Agents Are Only as Good as Their Reach

Agents Are Only as Good as Their Reach

When an agent can't reach your real systems, it guesses. The right tool access turns a demo into something your team relies on.

Validation Before the Build

Diesel Laptops

Fleet technicians were losing hours to manual searches across 160,000+ repair records, and that proprietary data could never leave their own infrastructure. Before building, we validated a self-hosted retrieval approach inside an AWS VPC. Lookup time dropped 85%, data residency held, and this Inc. 5000 company kept full custody of all its repair data.

160,000+

Repair Records

85%

Faster Lookup

AWS

Self-Hosted Infrastructure

Diesel Laptop

SmartMedHx

Clinical teams lost nearly an hour daily per provider to note-taking. We built a HIPAA-compliant RAG chatbot using LangGraph, interviewing patients, generating charts, and securing PHI within AWS VPC.

85%

Search Time Reduction

160,000+

Repair Records Indexed

12 Weeks

Build to Production

Extensiv

Extensiv teams waited days for engineer-driven data answers, slowing decisions. We built a LangGraph agent that interprets questions, queries operational databases, and delivers grounded insights in plain English.

90%+

SQL Accuracy

207

Tables

04

Databases

Extensiv
DRAG

What Clients Say About The Team

Fast-growing organisations do not applaud a consulting partner for polished slide presentations; they praise it for showing up when something actually breaks. The notes below come from founders who watched Kodexo Labs work the problem in real time.

Kodexo Labs has met all expectations; the team delivers on time and manages the project seamlessly. They respond promptly to needs and communicate effectively through virtual meetings, Google Chat, and WhatsApp. Overall, they're highly passionate about the project and excel in customer service.

Christopher Brigham

MD President, Brigham and Associates, Inc.

WATCH VIDEO

  • Secure EHR tool access
    HIPAA-ready connectors
    Audit-logged agent actions

MCP Development Services, Built For Every Industry You Run

Every industry runs on its core systems, and your agents stay useless until they reach them safely. We build MCP servers connecting to the exact tools each vertical depends on, with the access controls that industry demands.

Build a HIPAA-compliant, agentic, or omnichannel chatbot. Let's scope it.

Sector-specific platforms either compound their data advantage or fall behind the operators investing now. Find out where yours sits.

The Security And Compliance Standards Every MCP Server Meets

Handing agents access to your systems raises one question first: who can do what, and can you prove it later? Every MCP server we ship enforces strong authentication, scoped permissions, and encrypted transport from day one, mapped to the standards your auditors already check.

PCI-DSS

PCI-DSS

hipaa-logo

HIPAA

gdpr-compliance

GDPR

ccpa-compliance

CCPA

iso-27001

ISO 27001

NIST CSF

NIST CSF

SOC TYPE 2 Logo

SOC TYPE 2

FERPA Logo

FERPA

OWASP

COPPA Logo

COPPA

PCI-DSS

PCI-DSS

hipaa-logo

HIPAA

gdpr-compliance

GDPR

ccpa-compliance

CCPA

iso-27001

ISO 27001

NIST CSF

NIST CSF

SOC TYPE 2 Logo

SOC TYPE 2

FERPA Logo

FERPA

OWASP

COPPA Logo

COPPA

Why Teams Building With Model Context Protocol Pick Kodexo Labs For Production Work

Plenty of teams can demo an MCP server on a laptop. Far fewer have actually shipped agent tooling into regulated production systems and kept it running there. **That gap is exactly where our work lives.

Production-Grade Tool Integration, Not Prototypes

Most MCP demos fail the moment real production data hits them. We solved that for Extensiv, whose operations team now queries 207 tables across four databases in plain English at over 90% accuracy.

Vendor-Neutral by Design

MCP exists so your agent tools never marry one model vendor, and neither do we. We build across LangGraph, LangChain, and whatever fits. Switch from Claude to GPT-4o and your servers keep running.

cyber-security

Security Built In From Day One

Security bolted on late is how breaches start. In SmartMedHx, HIPAA shaped the design from day one. Now 42 providers log 493 patient interviews on that patent-pending system. Same bar for every MCP. 

Self-Hosted Where It Matters

Some data simply cannot leave your own walls. For Diesel Laptops, we ran the whole system in their own AWS VPC, cutting parts-lookup time 85% across 160,000 records with no data ever leaving.

Your Agents Already Have The Reasoning. Give Them The Reach.

Your Agents Already Have The Reasoning. Give Them The Reach.

A model that can think but cannot act is a very expensive chatbot. MCP is what turns your agents into systems that actually do the work your whole team is quietly drowning in.

Recognised, Not Self-Declared

These badges come from third-party platforms that audit real client engagements, not from our own marketing. Every one links to its source profile, so you can check yourself.

Top Clutch Machine Learning Company San Francisco 2026
Clutch Spring Champion 2024
Upwork Top 1% · Top Rated
Top Artificial Intelligence Company
Top Clutch Chatbot Company 2024 Award
Top Clutch Health Wellness App Developers Chicago 2026
Top Clutch Artificial Intelligence Company 2024 Award
Top Clutch Generative Ai Company 2024 Award
Top AI Development Company by Selected Firms
Top Artificial Intelligence Companies 2022 by TopAppFirms
Top Clutch Artificial Intelligence Company Chicago 2026
Top Clutch Machine Learning Company San Francisco 2026
Clutch Spring Champion 2024
Upwork Top 1% · Top Rated
Top Artificial Intelligence Company
Top Clutch Chatbot Company 2024 Award
Top Clutch Health Wellness App Developers Chicago 2026
Top Clutch Artificial Intelligence Company 2024 Award
Top Clutch Generative Ai Company 2024 Award
Top AI Development Company by Selected Firms
Top Artificial Intelligence Companies 2022 by TopAppFirms
Top Clutch Artificial Intelligence Company Chicago 2026

Overcoming MCP Development Challenges

The risk with MCP is not writing the server. It is what happens once real agents and real data hit it: security holes, lost context, brittle legacy links, and vendor lock-in. Here are the four failure modes we design against.

Problem

The Tool Poisoning Risk

A compromised or malicious tool definition can quietly instruct every connected agent to leak data, run unwanted actions, or exfiltrate credentials silently.

Solution

  • •

    We enforce scope-limited permissions so each tool touches only what its job requires.

  • •

    Signed tool manifests verify every single definition before an agent can load it.

  • •

    Runtime validation checks each call against policy and blocks anything that looks wrong.

Problem

Context Management At Scale

Long-running agent sessions lose track of state between tool calls, so agents repeat work, forget earlier steps, or act on stale information.

Solution

  • •

    Structured session memory keeps each agent's state consistent across every call it makes.

  • •

    Capability negotiation lets host and server agree upfront on exactly what each supports.

  • •

    Explicit lifecycle management opens, tracks, and closes every session cleanly, leaving nothing hanging.

Problem

Legacy System Integration Gaps

Decades-old ERP and mainframe systems expose no modern API, so connecting agents to them usually means a costly rebuild nobody budgeted for.

Solution

  • •

    An MCP wrapper gives old systems a clean interface without touching core code.

  • •

    A phased rollout migrates one system at a time, so nothing breaks overnight.

  • •

    Zero-downtime cutover keeps the legacy system live until the MCP layer replaces it.

Problem

The Cross-Vendor Lock-In Trap

Agent logic hard-coded to one model provider's tool format traps you: switching vendors later means rewriting every single integration you already shipped.

Solution

  • •

    Vendor-neutral MCP servers speak one open standard, so no provider owns your tooling.

  • •

    Model-agnostic client design lets you swap Claude for GPT-4o without rewriting anything downstream.

  • •

    Portable tool definitions move with you between providers, protecting the work you funded.

Problem

The Tool Poisoning Risk

A compromised or malicious tool definition can quietly instruct every connected agent to leak data, run unwanted actions, or exfiltrate credentials silently.

Solution

  • •

    We enforce scope-limited permissions so each tool touches only what its job requires.

  • •

    Signed tool manifests verify every single definition before an agent can load it.

  • •

    Runtime validation checks each call against policy and blocks anything that looks wrong.

Problem

Context Management At Scale

Long-running agent sessions lose track of state between tool calls, so agents repeat work, forget earlier steps, or act on stale information.

Solution

  • •

    Structured session memory keeps each agent's state consistent across every call it makes.

  • •

    Capability negotiation lets host and server agree upfront on exactly what each supports.

  • •

    Explicit lifecycle management opens, tracks, and closes every session cleanly, leaving nothing hanging.

Problem

Legacy System Integration Gaps

Decades-old ERP and mainframe systems expose no modern API, so connecting agents to them usually means a costly rebuild nobody budgeted for.

Solution

  • •

    An MCP wrapper gives old systems a clean interface without touching core code.

  • •

    A phased rollout migrates one system at a time, so nothing breaks overnight.

  • •

    Zero-downtime cutover keeps the legacy system live until the MCP layer replaces it.

Problem

The Cross-Vendor Lock-In Trap

Agent logic hard-coded to one model provider's tool format traps you: switching vendors later means rewriting every single integration you already shipped.

Solution

  • •

    Vendor-neutral MCP servers speak one open standard, so no provider owns your tooling.

  • •

    Model-agnostic client design lets you swap Claude for GPT-4o without rewriting anything downstream.

  • •

    Portable tool definitions move with you between providers, protecting the work you funded.

Every tool listed is in active production on a Kodexo Labs.

Every framework, runtime, and cloud service named here is running on a live client product right now. No theoretical stack, no resume keywords, no tools added for marketing weight.

Python
Python

How We Take Your MCP Server Live

1

Discovery And Mapping

We map every tool, data source, and internal system your agents must reach, then rank them by priority and sensitivity. You leave this phase with a scoped plan before any server code is written.

2

Server Architecture Design

Next we design the server and client structure and pick the right transport, STDIO for local tools or HTTP with SSE for networked ones. You approve the shape of the system before we build it.

Design & Prototyping
3

Build And Implementation

Then we implement the server in Python, TypeScript, or Go, carefully defining each tool, resource, and prompt against the JSON-RPC spec. Every capability is wired to a real system and demoed live at sprint end.


Development and Integration
4

Security And Hardening

Here we lock down access with OAuth 2.1, scope every permission to least privilege, add mTLS, and turn on audit logging. Your security team reviews the whole surface before anything ships to production.

5

Deploy And Handoff

Finally we roll out in stages, watching latency and failure rates through live tracing, then hand over full documentation and monitoring so your own internal team can run and extend the server with confidence.


Insights From The Kodexo Labs Team

What Is Agentic AI? Definition, Types and Examples

July 2025 · By Aruba Yousuf

Discover what agentic AI is, its core definitions, types, and real-world examples. This guide explores how autonomous AI agents revolutionize business through proactive decision-making, environmental adaptation, and continuous learning across industries like finance, healthcare, and manufacturing.

What Is Model Context Protocol (MCP) and Why It’s the Future of AI Context Management

July 2025 · By Aruba Yousuf

Explore the Model Context Protocol (MCP), an open-source standard launched by Anthropic for AI systems to access tools, APIs, and live data. Learn how MCP solves the M×N integration problem, enables agentic AI, and powers scalable, secure workflows with real-time data access. Ideal for developers, CTOs, and enterprises building intelligent systems in 2025.

top 10 AI agents for content generation in 2025

Top 10 AI Agents for Content Generation in 2025

September 2025 · By Kodexo Labs

This comprehensive guide explores the top 10 AI agents for content generation in 2025, helping businesses, developers, and content creators choose the right tools for their specific needs. From Google Gemini to specialized platforms, discover how these AI systems transform content creation workflows.

Frequently Asked Questions

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Still have questions about your MCP build?

Talk to Our AI Team

MCP implementation services cover the design, build, and hardening of Model Context Protocol servers, the open standard that lets AI agents reach your tools and data through one consistent interface. In practice that means connecting agents to the systems your business already runs, safely and with full logging. Kodexo Labs has shipped 51 AI-powered products across 25+ industries, and brings that same production track record to MCP work.