Model Context Protocol is an open standard for exposing tools, data and prompts to AI systems. A custom MCP server is needed when the capability an agent must reach is your own: an internal system, a proprietary dataset or a specific chain. LimeChain builds them as production infrastructure, with strict tool schemas, least-privilege access, audit logging and state-changing tools treated as high impact by default.
Every engagement runs the same sequence, treating the server as production infrastructure rather than demo glue.
Which agents and users, which services and chains, which actions, which environments, and what auditability is required.
Which resources, prompts and tools belong in the server, what stays out, and how state, upgrades and decommissioning work.
Schemas, deterministic validation, authentication and authorization, least privilege, secrets and signing boundaries, rate and cost controls.
The hardest service or chain interaction is built first and exercised with a real MCP client, reviewed weekly.
Contract tests, malformed and adversarial inputs, permission boundaries, prompt-injection paths, idempotency, retries and dependency outages.
Packaged with configuration, observability, audit logs, versioning and runbooks, with high-impact tools kept approval-gated.
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