Database modernisation and synthetic data company, LangGrant, unveils the LLM enterprise database orchestration and governance engine (LEDGE) MCP server. This platform enables large language models (LLMs) to reason across multiple databases at scale, execute accurate multi-step analytics plans, and accelerate agentic AI development. LangGrants assured that the LEDGE MCP server does not send data to the LLM or breach governed boundaries.
“The LEDGE MCP Server removes the friction between LLMs and enterprise data,” said Ramesh Parameswaran, CEO, CTO, and co-founder of LangGrants. “With this release, enterprises can apply agentic AI directly to existing database environments like Oracle, SQL Server, Postgres, Snowflake — securely, cost-effectively, and with full human oversight.”
LEDGE MCP Server
The offering aims to address barriers when applying LLMs and AI assistants to operational databases, including security and governance policies, escalating token and compute costs, and safely cloning complex enterprise databases. Moreover, databases are not designed for LLM consumption, and problems arise from the tedious manual process of context engineering.
The LangGrant LEDGE MCP Server claims to support limitless agents from any vendor. It claims to provide the following five foundational capabilities:
- LLM Governance
- Token Dashboards & Budgeting
- Accurate Multi-Step Analytics Plans
- On-Demand Database Cloning and Containers for Agent Development
- Complete Automated Database Context at Scale
“The LEDGE MCP Server removes friction between LLMs and enterprise data. Enterprises can apply agentic AI directly to database environments securely, cost-effectively, and with full human oversight,” saidParameswaran.
