Model Context Protocol · robust integrations between LLMs and your systems
We design and implement MCP servers (Model Context Protocol) that expose your enterprise systems (ERP, CRM, DB, own APIs) to LLM agents from Claude, GPT and others. With strict validation, permission control and audit.
We publish this list to qualify together if we fit. If not, we save you time.
We identify which systems to expose (ERP, CRM, DB, APIs, filesystem, own tools), which operations are safe vs sensitive, and permissions matrix per agent/role.
MCP server with official Anthropic SDK (Python/TypeScript). Tool definitions with strict Pydantic/Zod schemas. Authentication, rate limiting, structured logging.
Server connection with Claude Desktop, Claude Code or own agents. Automated test suite. Agent decision evaluation with human in the loop.
Deployment in your infra (Docker/K8s/serverless per case). Usage dashboard, cost per tool, anomaly alerts. Operational documentation.
Invented cases with metrics consistent with our real ranges.
Server exposing core queries, report generation and KYC validation to Claude agents for operations team. Granular audit of every call.
Server with access to logs, feature flags, test database and CI/CD for engineering team Claude Code. Reduces bug and regression investigation time.
Server with access to proposals repository, historical cases, templates and market studies. Consultants do semantic search from Claude Desktop.
MCP (Model Context Protocol) is an open standard from Anthropic (2024) defining how LLMs connect to external systems. Advantage over direct integration: a single standard protocol reusable by multiple agents/clients (Claude Desktop, Claude Code, own agents, other MCP-compatible tools).
With direct integration each agent reimplements connection to each system. With MCP the server is implemented once and any MCP-compatible client consumes it. As the MCP ecosystem grows (Anthropic, IDEs, agent platforms), this approach scales much better.
Trade-off: for 1-2 point tools, direct integration is simpler. MCP makes sense when tool count grows or there are multiple consumers of the same server.
MCP was created by Anthropic but is an open standard. Today Claude (Desktop, Code, API) is the most mature consumer. Other clients are adopting it: Cursor, Zed and various agent platforms support it.
GPT and Gemini don't support it natively yet (August 2026) — they use their own systems (function calling, GPTs, extensions). It's possible to build MCP → OpenAI function calling adapters, but it's not native.
Our recommendation: if going all-in with Anthropic ecosystem, MCP is natural. If multi-model, consider exposing the same systems via multiple protocols (MCP + OpenAI functions + classic REST) from a common backend.
Three layers: (1) strong MCP client authentication (OAuth 2.0 or mTLS), (2) granular authorisation per tool (permission matrix per role/agent), (3) strict input validation with Pydantic/Zod schemas rejecting any malformed or out-of-range request.
Additionally: per-client/tool rate limiting, logging of all calls with full context (which agent, which tool, which parameters, which result), and exportable audit for compliance review.
For tools performing sensitive actions (payments, client notifications, master data changes), we always design human-in-the-loop via agent interruption or explicit confirmation.
Typical pilot (MCP server + 2-3 exposed systems + Claude integration + observability): €25-60k in 4-8 weeks. Minimum monthly operating cost (infra + monitoring): €200-800/month depending on volume.
For more complex servers (10+ systems, fine governance, high availability, regulatory requirements): €60-150k and €800-2,500/month operational.
Free 30-min diagnosis with architecture, timing and budget estimate for your specific case.