LangGrant Launches LLM enterprise database orchestration and governance engine (LEDGE) MCP Server

LEDGE MCP Server does not expose data to LLMs, removes token costs as a barrier to Agentic AI, and delivers accurate, executable multi-step analytics plans.

BELLEVUE, WASH. , CA, UNITED STATES, December 9, 2025 /EINPresswire.com/ -- LangGrant (earlier known as Windocks), a leader in database modernization and synthetic data, today announced the launch of the LEDGE MCP server, a first-of-its-kind platform that enables LLMs to reason across multiple databases at scale, execute accurate multi-step analytics plans, and accelerate agentic AI development — all without sending data to the LLM or breaching governed boundaries. This enables LLMs to deliver accurate results for analytical queries in minutes, a task that usually takes weeks, even with AI-powered coding tools.

“The LEDGE MCP Server removes the friction between LLMs and enterprise data,” said Ramesh Parameswaran, LangGrants’ CEO, CTO, and co-founder. “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.”

Enabling AI with Enterprise Database Ecosystems

Context engineering is rapidly emerging as a foundational discipline in the AI era — especially as agentic systems and LLM-driven automation move from demos to production. However, several technical challenges must be addressed to fully unlock its potential in leveraging existing enterprise data assets within a modern AI architecture.

Enterprises have rapidly adopted LLMs and AI assistants, yet face five persistent barriers when applying them to operational databases:
● Security and governance policies block LLM adoption: Since most enterprises cannot permit direct access to or data movement outside governed systems, the use of LLMs can be limited.
● Token and compute costs escalate as organizations push raw data: This data can sometimes include millions of rows into LLMs for analysis.
● Agent developers need production-like data: This is required to build and test models —but they lack a safe, on-demand way to clone complex enterprise databases.
● Databases are not designed for LLM consumption: They are massive, complex, and unintuitive. Business users frequently need to join tables, but even LLMs with extended context windows struggle to handle that scale or maintain accuracy.
● Software engineers are only doing manual context engineering: Writing queries and data pipelines with tools like Co-Pilot is a very manual process wherein you are providing context in bits & pieces to the LLM, which takes weeks.

The LangGrant LEDGE MCP Server enables limitless agent support, with any agent from any vendor. These challenges are addressed through five foundational capabilities:
● LLM Governance - LEDGE orchestrates LLMs to deliver results accurately while still complying with enterprise data policies.
● Token Dashboards & Budgeting - Analytics and reasoning occur using metadata and schema context — no raw data or large payloads are transmitted to the LLM. This dramatically lowers token costs, eliminates API-billing friction, and enables practical scale for enterprise agentic AI.
● Accurate Multi-Step Analytics Plans - LEDGE MCP automates query planning and orchestration, generating precise, multi-stage analytics workflows autonomously — while remaining fully reviewable and auditable by human teams. This eliminates weeks of manual scripting and reduces LLM hallucination risk in query generation.
● On-Demand Database Cloning and Containers for Agent Development - Agent developers can instantly provision production-like, isolated clones and containers for developing, testing, and tuning AI agents — all without impacting live databases or creating uncontrolled copies.
● Complete Automated Database Context at Scale - LLMs can now comprehend and reason across multiple heterogeneous databases. The LEDGE MCP Server automatically maps schemas, relationships, and metadata— letting LLMs “see” the entire data landscape without reading the underlying data.

These capabilities make the LEDGE MCP Server an ideal solution for a broad range of use cases and Agentic solutions. The LangGrant LEDGE MCP Server is now available for trial. Teams can experience automated context engineering, multi-database reasoning, and secure agentic AI development firsthand at www.LangGrant.com.

About LangGrant
LangGrant is a leader in database modernization, cloning, and synthetic data. In 2015, the company pioneered the first-ever SQL server container on Windows (using Docker technology). In 2017, LangGrant released the first Docker containers with Oracle database clones. Gartner has recognized LangGrant for synthetic data and continuous integration & deployment for databases. For more information, visit www.LangGrant.com
Third-party trademarks mentioned are the property of their respective owners.

###

Jay Nichols
Nichols Communications for LangGrant
+1 408-772-1551
jay@nicholscomm.com
Visit us on social media:
LinkedIn

Legal Disclaimer:

EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.