Connect your tools
to the AI brain.
We build Model Context Protocol servers so AI assistants — Claude, Cursor, ChatGPT — can securely access your databases, APIs and internal systems. The missing layer between AI and the enterprise.
The protocol that connects AI and the enterprise.
MCP is the open standard (created by Anthropic) that lets an AI model read documents, query databases or execute actions inside your stack — with clear permissions and traceability. We build the MCP servers you need to use Claude or Cursor with your data, without it leaving your perimeter.
When it's the right tool:
- You want your team to query internal data (CRM, database, wiki) directly from Claude or Cursor.
- You have internal APIs you'd like to expose to an AI assistant without rewriting them as 'tools' in every project.
- You need a control layer between AI and enterprise systems, with auth, logs and granular revocation.
- You're building a product that wants to offer integration with Claude Desktop, Cursor or other MCP clients.
What we build
Custom MCP servers that connect AI to your company's operational reality.
MCP for CRMs
Servers for Salesforce, HubSpot, Pipedrive — so AI can read and update customer data with permissions.
MCP for databases
Secure access to Postgres, MySQL, BigQuery or data warehouses, with restricted queries and auditing.
MCP for internal APIs
Wrappers around your APIs so a model can invoke them as tools, without exposing credentials.
Knowledge MCP
Servers that index wikis, drives, Notion or Confluence with per-user permissions respected.
Action MCP
Servers that let AI execute actions: create tickets, send emails, update records, with confirmation.
Distribution & security
Packaging, distribution (Smithery, npm, private registries), OAuth auth and usage policies.
How we build it
The sequence of work. Timing adapts to the project's scope — always tailored.
Case analysis
We understand what needs to be exposed, what permissions are required and which MCP clients will use it.
Server design
We define tools, resources, prompts and auth policies.
Build & test
Implement in TypeScript or Python, with regression tests and validation against Claude/Cursor.
Launch
Deployment in your environment, client distribution and documentation for your team.