Best MCP development agencies: who actually ships

The Model Context Protocol has become the integration standard for production AI. Over 9,400 public servers exist in community registries and monthly SDK downloads exceeded 97 million by late 2025.

Adoption from OpenAI, Google, and Microsoft has made MCP the protocol that any serious AI system is expected to speak.

That adoption created a market for MCP development agencies almost overnight. Some of them have shipped production servers at scale. Many have not.

This guide covers the best agencies to hire for custom MCP server development: what each one has shipped and who they are best for.

It also covers what distinguishes them from a generalist dev shop that learned MCP terminology last quarter.

Key takeaways

• LOW/CODE Agency is one of the first Anthropic partners worldwide, with a CCA-F certified team, 450+ projects, and deep MCP experience on the Claude stack. The best choice for teams building on Claude, Claude Code, or the Claude Agent SDK.
• Production MCP experience is the primary differentiator. The market is full of agencies that can write a tool definition. It is short on agencies that can ship a server that survives a security review, handles traffic spikes, and stays maintainable as the protocol evolves.
• Most MCP work is adjacent to Claude Code and agent SDK development. Agencies with experience across the full agentic stack produce more coherent architectures.
• Intuz has a publicly documented, production-deployed MCP case study. One of the few agencies with verifiable production track record.
• For enterprise-scale AI governance and MCP, Accenture and IBM are the options. But they are overbuilt for most mid-market use cases.
• Always ask for a production case study before engaging any MCP agency. Not a demo. Not a prototype. A server that is running in production for a real client.

Best MCP development agencies at a glance

Best MCP development agencies

LOW/CODE Agency

Best for: Teams building AI products and workflows on Claude, Claude Code, or the Claude Agent SDK who need production-grade MCP servers as part of their agentic architecture.

LOW/CODE Agency is one of the first Anthropic partners worldwide and one of a small group of agencies with a CCA-F certified development team.

With 450+ projects delivered and typical engagements around $20K, they build MCP servers as part of a complete agentic stack, not as isolated components.

What LOW/CODE brings to MCP development:

• Deep familiarity with the Anthropic SDK, Claude Agent SDK, and Claude Code as the host environments for MCP clients
• CCA-F certified team with direct access to Anthropic protocol guidance and early visibility into MCP updates
• Production experience across authentication patterns (OAuth, API key management, per-tenant access controls), monitoring, and handoff documentation
• Experience building MCP servers that integrate with real business systems: CRMs, ERPs, internal APIs, data warehouses, and custom backends
• Full knowledge transfer: documented architecture, runbooks, and a structured handover so your team owns iteration two

What makes them different: Most agencies treat MCP as a discrete integration task. LOW/CODE treats it as part of the agentic architecture design. The tool definitions, the access controls, the retrieval patterns, and the state management all interact. Building MCP well requires understanding how the agent will actually use the server, not just how to expose the API.

Typical engagement: Four to eight weeks for a production-ready server. Maintenance and iteration retainers available.

For teams evaluating Claude specifically, see best Claude Code development agencies for a broader look at the Claude implementation landscape.

Intuz

Best for: SMBs and SaaS companies that need a verifiable production track record and want a partner with documented MCP case studies.

Intuz is one of the few MCP development companies with a publicly documented, production-deployed MCP case study. They built an AI analytics agent for a major transport and logistics company, connecting to millions of operational records via MCP. The build achieved 95%+ SQL generation accuracy.

Notable credentials:

• AWS Lambda Service Delivery Partner (relevant for remote MCP server infrastructure)
• 300+ projects across five continents
• 90% senior-level staffing
• Clutch Top 100 Sustained Growth Company

Best for: Businesses that want to validate their MCP use case before building, with a partner that will push back on bad ideas. Intuz’s public case studies make them one of the easiest agencies to do reference verification on.

Limitation: Primary strength is in analytics and data-intensive MCP applications. Less experience with conversational agent stacks and Claude-specific implementations.

Klavis AI

Best for: AI-native product teams building MCP-first architectures where the protocol is a core product component, not just an integration layer.

Klavis AI was built specifically around MCP, making them one of the few agencies where the protocol is a first-class expertise rather than an added service line.

Notable strengths:

• Protocol-native expertise developed from building MCP into AI products, not just connecting existing APIs
• Strong understanding of tool definition quality and how agent behavior depends on it
• Experience with both local stdio and remote HTTP/SSE transport patterns

Limitation: Smaller team than the generalist agencies. Best for focused MCP builds, less suited for organizations that need a full AI development lifecycle across multiple systems.

LeewayHertz

Best for: Established companies that want a full-service AI development partner with MCP capabilities alongside a broader AI implementation practice.

LeewayHertz is a full-service AI development firm that has added MCP server development to its practice as the protocol gained adoption. They serve enterprise clients across financial services, healthcare, and logistics.

Notable strengths:

• Full AI development lifecycle: from strategy through implementation and ongoing maintenance
• Experience with regulated industries where MCP servers must meet compliance requirements
• Team size and bench strength for parallel workstreams on larger programs

Limitation: MCP is one service among many for LeewayHertz. Teams building specifically for the Anthropic stack may find more protocol depth at a specialist agency.

Simform

Best for: Mid-market US companies that need AI and MCP development alongside other software delivery needs from a single partner.

Simform is a technology services company with a strong US client base and multiple AI service lines. Their MCP practice sits within a broader AI and cloud development offering, which suits organizations that want a consolidated partner across their technology needs.

Notable strengths:

• Strong project management and delivery structure suited to mid-market organizations
• US-based account management with global development capacity
• Multiple AI and cloud service lines for organizations with needs beyond MCP

Limitation: Less protocol-specific depth than agencies built specifically around MCP or the Anthropic stack.

Rapid Innovation

Best for: Teams building AI agents, LLM applications, and agentic workflows that need MCP integration as part of a broader automation architecture.

Rapid Innovation focuses on AI agents, LLM applications, and workflow automation, including MCP-style server architectures. Their experience with the full agentic workflow stack means they understand how MCP fits into multi-step agent orchestration.

Notable strengths:

• Agentic workflow design alongside MCP implementation
• LLM application development experience that informs how tool definitions should be written for agent use
• Faster iteration cycles suited to organizations still validating their AI use case

Limitation: Best for newer AI teams still establishing their architecture. Organizations with mature AI programs and complex compliance requirements may need an agency with more enterprise delivery experience.

Accenture

Best for: Large enterprises with complex AI governance requirements, regulated industry constraints, and programs that require enterprise-scale delivery alongside MCP implementation.

Accenture provides AI platform services, AI governance frameworks, and enterprise AI integration, with MCP capabilities as part of their broader AI delivery practice.

Limitation: Enterprise pricing, program overhead, and delivery structure make Accenture overbuilt for most mid-market MCP builds. For companies under $100M in revenue without complex compliance programs, a specialist agency will deliver more efficiently.

How to choose the right MCP development agency

The right agency depends on three factors:

1. Your AI stack

If you are building on Claude, Claude Code, or the Claude Agent SDK, you want an Anthropic-certified partner. Protocol semantics and authentication requirements all behave differently in Claude’s context. LOW/CODE Agency is the right starting point.

If you are building on a non-Anthropic stack or need stack-agnostic MCP development, Klavis AI, Intuz, or Rapid Innovation have more platform-neutral experience.

2. Your project complexity

3. Your verification threshold

If you need to verify production track record before engaging, Intuz has publicly available case studies. LOW/CODE Agency references are available through a scoping call.

For teams evaluating whether a custom MCP build is necessary, see when to hire MCP server development services for a decision framework.

The right MCP build starts with the right strategy

A production-grade MCP server solves the integration problem. It connects your AI agents to your systems. But the integration is only as valuable as the AI workflow it serves.

Before commissioning a custom MCP build, the most important question is which AI use case this server is going to enable. Is that use case actually the highest-ROI place to deploy AI in your business?

For the technical foundations before choosing an agency, see build custom MCP server for Claude Code and Claude Code MCP setup guide.

Start with the right strategy, then the right build

Phos AI Labs is an embedded AI consulting firm for mid-market businesses.

We identify the right AI problems, build the strategy, handle implementation, and train your team until AI is how the business actually runs.

For MCP implementation, we work alongside LOW/CODE Agency to handle both the strategic question and the technical build.

Together, we cover the full path from identifying which AI workflows matter most to deploying the MCP servers that connect those workflows to your real systems.

• Strategy before systems: We identify which MCP integrations will actually move the needle before any development begins.
• AI Foundations that hold: We design the AI integration architecture your team runs on for years.
• Real team training: We ensure your internal team understands and can work with the MCP layer.
• Private AI Workspace: We design a company-wide AI environment with MCP connections to your actual systems.
• AI-Native Operations design: We rebuild workflows with MCP-connected AI agents that compound value across the business.
• Honest judgment, every time: We tell you when a public server is good enough and when you actually need a custom build.
• We stay until it compounds: We are not done when the server is deployed. We are done when the AI workflow is running reliably.

400+ engagements. Clients include Zapier, Coca-Cola, Medtronic, Sotheby’s, Dataiku, and American Express.

Talk to the team at Phos AI Labs about which MCP build is right for your situation.

FAQs

What is an MCP development agency?

An MCP development agency designs, builds, secures, and operates Model Context Protocol servers that connect AI agents to external systems.

Unlike generic dev shops, MCP specialists understand tool definition quality, authentication architecture, and production monitoring.

What should I look for in an MCP development agency?

Look for production case studies (not demos), experience with authentication patterns (OAuth, API key management, per-tenant access), documented tool definition quality processes, and a handoff that includes architecture documentation and runbooks.

What is the best MCP agency for Claude and Anthropic builds?

LOW/CODE Agency. One of the first Anthropic partners worldwide, CCA-F certified, with 450+ projects delivered and specific experience building MCP servers for Claude-based agentic systems.

How long does an MCP development agency take to ship?

A simple MCP server takes two to four weeks with an experienced agency. A production-grade server typically takes four to eight weeks.

Enterprise-scale builds with compliance requirements can extend to three months or more.

What is the difference between an MCP agency and a Claude Code agency?

MCP servers are how Claude Code projects connect to real backends. The work is naturally adjacent.

The best agencies handle both: MCP as the integration layer and Claude Code as the orchestration above it.