We connect Claude to your entire revenue stack using Model Context Protocol - giving your team a natural language interface to live business data. No SQL. No analysts. No waiting.
Model Context Protocol is an open standard developed by Anthropic that lets AI models like Claude connect directly to external tools and data sources. Rather than asking Claude a question based on training data, MCP lets Claude query your actual systems in real time - your CRM, your accounting platform, your operational databases - and return answers grounded in current data.
We build MCP servers for your revenue and operational stack, then expose them to Claude through a secure interface. Your team types a question in plain English and gets an answer drawn directly from live records. No dashboards to log in to. No SQL to write. No waiting for an analyst to pull the data and format it into a report.
Dashboards answer the questions you thought to ask when you built them. They are a snapshot of the questions you expected your business to need answered in the future. The moment a stakeholder asks something new - what is our net new ARR by segment this week compared to last month, which accounts in the enterprise tier have not had an activity in 30 days, what is the average days-to-close for deals sourced through LinkedIn this quarter - someone needs to write a query or ask an analyst and wait.
That delay compounds. A question asked on Monday becomes a decision made on Friday with Thursday's data. MCP removes that bottleneck entirely. Any question your data can answer, your team can now ask directly and get an answer in seconds.
MCP server implementations that connect Claude to your existing stack. We handle every layer: authentication and authorisation so Claude only accesses what it should, data normalisation so figures from different systems are comparable, query optimisation so responses are fast even against large data sets, and response formatting so the output Claude returns is readable and actionable.
We also build the prompting layer - the system instructions that ensure Claude interprets questions correctly for your business context. "Revenue" means something specific in your business. "Active client" has a definition. "Pipeline" has a stage filter. We encode that context so your team gets consistent, accurate answers without needing to phrase every question precisely.
We start with a data audit. We map what systems you have, what data lives where, what the relationships between systems are, and what questions your team most frequently needs to answer. That audit shapes which MCP endpoints we build first and how we prioritise the integration work.
We then build and test MCP server endpoints for each connected source, validating responses against known-correct data before anything goes live. The validation phase is not optional - we run each endpoint against historical data where we know the correct answer, then diff the output until the numbers match. After that, we train your team on how to use the interface effectively and run a two-week observation period.
If a system has an API or a queryable database, we can connect it. The most common integrations we build are into HubSpot, Salesforce, QuickBooks, Xero, Google Sheets, and custom PostgreSQL or MySQL databases. For operational data, we connect to project management tools, support platforms, and internal APIs built on your existing infrastructure.
Finance teams who need fast, accurate answers without opening a spreadsheet. Founders and CEOs who want operational awareness on demand without building a full analytics function or waiting for a weekly report. Sales leaders who need pipeline intelligence in the middle of a board call, not scheduled for Tuesday afternoon.
The common profile is a business that has good data in multiple systems but no clean way to ask questions across all of them simultaneously. MCP solves the integration layer at the intelligence level - not by building another dashboard, but by giving your team a conversational interface to every system at once.