MCP Server Development

Your data,
connected to AI.

Without live access to your data, your AI assistant is guessing — even when it sounds certain. We build bespoke MCP servers that give your AI assistant read-only, plain-language access to your actual database or API. Scoped to your setup. Delivered in weeks.

Book a Discovery Call → How It Works ↓
What Is MCP?

The connection layer between your data and AI

MCP (Model Context Protocol) is the open standard — backed by Anthropic, adopted by Claude, Cursor, and others — for giving AI assistants structured, real-time access to external data and tools. Instead of pasting spreadsheet exports into a chat window, the assistant queries your live data through defined, auditable tools.

We build the MCP server. You get an AI assistant that actually knows your business.

Your data. Your AI. No engineering overhead.

The Challenge

Your AI assistant is flying blind

  • AI answers data questions instantly — and wrongly
  • General knowledge models hallucinate in your context
  • Analysts remain bottlenecks for routine data questions
  • Answers can't be traced to your actual business numbers
  • The gap isn't model capability — it's access
Valinor AI

Grounded answers. Every time.

  • Live read-only access to your database or API
  • Answers traceable to real data, not model priors
  • Plain-language queries — no SQL required from users
  • Your AI becomes operational, not just conversational
  • No new infrastructure. No replatforming.
Capabilities

What we connect

Any data source with a query interface. Any AI assistant that supports MCP.

Database Connectors

PostgreSQL, MySQL, BigQuery, Snowflake, Redshift. Read-only query tools with schema-aware natural language translation — the assistant asks in plain English, the server handles the SQL.

PostgreSQLBigQuerySnowflakeMySQLRedshift

REST API Connectors

Any authenticated REST API mapped to structured MCP tools — CRM, ERP, ticketing, analytics platforms, and internal services. We document the tool schema so the assistant knows what to ask.

REST APIsOAuthAPI KeysWebhooks

BI & Semantic Layer

Connect your dbt semantic layer or BI metadata so the assistant understands your defined metric logic — not raw table columns. Answers grounded in your governed definitions.

dbtLookerMetabaseSemantic Layer

Multi-Source Builds

Two or more sources unified into one MCP server, with a coherent tool schema and cross-source query support. For when the answer requires joining your CRM with your data warehouse.

Custom BuildMulti-sourceEnterprise
How We Work

From discovery to deployed server

A lean, transparent process. Direct access to the practitioner doing the work at every stage.

Discovery Call

We scope your data sources, AI assistant, use cases, and security requirements. Typically 30 minutes. We'll tell you clearly whether your stack is a fit — and if not, what would make it one.

Schema Review & Design

We audit your data model, define tool schemas, and agree on read boundaries and safety guardrails before writing a line of code. You review and sign off before we build.

Build & Test

Bespoke MCP server built and tested against your real data. Includes authentication, rate limiting, error handling, and query safety constraints. You test it against your actual use cases.

Handover

Deployed to your infrastructure with source code, configuration files, and documentation. You own it — built for your team to operate independently. No ongoing dependency on us.

Frequently Asked Questions

Common questions

If your question isn't here, the discovery call is the right place to ask it.

What is a custom MCP server?
An MCP (Model Context Protocol) server is a lightweight service that exposes your data or APIs to an AI assistant through a defined, auditable tool interface. Instead of the assistant guessing from general knowledge, it queries your live data directly. We build custom MCP servers tailored to your specific data schema and use cases.
The standard way is through an MCP server — a secure translation layer between your database and the AI assistant. We handle the design, build, and deployment so your team doesn't need to write or maintain the integration code.
Any database with a standard query interface — PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, and others — and any authenticated REST API. We confirm your specific stack on the discovery call.
MCP servers are read-only by design — the assistant cannot write to your data. Data is only accessed during a specific query and is not retained, stored, or used for model training. We scope query boundaries explicitly as part of the design process.
Most single-source builds — one database or API — take 2–4 weeks from discovery call to handover. Multi-source or enterprise builds typically take 4–6 weeks depending on complexity.
Get in Touch

Ready to connect your data?

Start with a 30-minute discovery call — no obligation. We'll scope your data sources, confirm feasibility, and tell you exactly what's possible with your stack.

Book a Discovery Call → hello@valinorai.com

Remote-first  ·  Typical response within one business day

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