Challenge
Cases Financial agent on MCP, SQL, and executable skills How KT.Team moved OSNO-VA’s financial logic from spreadsheets to MCP, SQL, and executable skills for AI agents. 2026-06-04 Discuss the project Key takeaways How KT.Team moved OSNO-VA’s financial logic from spreadsheets to MCP, SQL, and executable skills for AI agents. OSNO-VA needed to give AI agents reliable access to financial data and calculation logic.
This approach lets users maintain financial logic without constant engineer involvement, while the agent can perform checks and calculations under reproducible rules. Task OSNO-VA needed to give AI agents reliable access to financial data and calculation logic. The spreadsheet approach proved too fragile for an agentic scenario: limits, retries, and brittle logic hurt speed and reliability.
Solution
KT.Team separated the general-purpose data platform and the organization’s financial skills: data is translated into SQL/databases, the agent gets access through MCP, and calculation business logic is moved into executable skills and scripts. Financial AI agent gets data through MCP Solution This approach lets users maintain financial logic without constant engineer involvement, while the agent can perform checks and calculations under reproducible rules.
Result - an AI-native financial stack where the agent does not just read a spreadsheet, but calls verifiable tools, gets data through MCP, and works with governed calculation logic.
Results
Blog Topics All articles 23.7.2026 AI accountant for a chain: how to automate revenue reconciliation 23.7.2026 How much an AI agent costs: what drives price and TCO 16.7.2026 AI for accountants: what it can do in 2026, whether it can replace them, and how to use it 27.6.2026 LLM capabilities in 2026: what to choose for your process and budget 19.6.2026 DORA 2026: AI does not deliver ROI - your process does
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