Pylar

Pylar is an MCP server and data access layer that connects AI agents to relational databases, cloud warehouses, and SaaS applications through governed SQL views. It allows engineering, data, and operations teams to bridge external systems like Snowflake, BigQuery, PostgreSQL, MySQL, Supabase, HubSpot, and Salesforce without granting agents raw, direct database access. Users define SQL views in Pylar's control plane to filter sensitive fields and join records across distinct data platforms, then generate Model Context Protocol tools using natural language prompts or manual configurations. These published tools provide standardized endpoints that AI clients can invoke to run controlled queries and access operational metrics. Because Pylar manages credentials and data boundaries within a centralized interface, administrators can modify data structures or security policies without redeploying connected agents. The platform also records queries and tool usage in a built-in evaluation dashboard, giving teams observability over agent queries, errors, and performance.

Category: AI & LLM Tooling

Tags: agent-framework, control-plane, data-integration, SQL

Visit Pylar

How to install and configure Pylar

To configure Pylar with an MCP client, follow these steps using the credentials provided in the Pylar management platform: 1. Sign up and connect your data sources (such as PostgreSQL, Snowflake, or HubSpot) inside the Pylar dashboard. 2. Create your governed data views using Pylar's SQL IDE to specify the exact schema and data agents can access. 3. Build your custom MCP tools manually or via natural language prompts, then publish them to receive your MCP credentials. 4. Open your client's configuration file, such as claude_desktop_config.json for Claude Desktop or the configuration settings in Cursor, LangGraph, or n8n. 5. Register the Pylar MCP server connection details and credentials according to the documentation provided in the Pylar console, then restart your MCP client.

What you can do with Pylar

• Creating governed customer support tools that query user histories, orders, and support tickets across PostgreSQL and HubSpot without exposing raw tables. - Joining cross-database pipeline records from Salesforce and Snowflake into a unified tool for AI-driven revenue forecasting. - Building marketing analysis tools that compute multi-touch attribution and campaign performance across disparate warehouse tables and Google Sheets. - Monitoring agent data interactions and identifying SQL query errors through the built-in Pylar Evals observability dashboard. - Delivering read-only product analytics to Cursor or Claude Desktop by building natural language generated tools on BigQuery data.

Key facts

• AI & LLM Tooling, Databases & Data Stores, Developer Tools & Code Intelligence
• agent-framework, control-plane, data-integration, SQL

Part of MCP Servers

What is Pylar?

Pylar is a secure data access platform and MCP server that enables AI agents to query structured data sources. It lets teams write SQL views over databases and SaaS applications, generate custom MCP tools, and deploy them to agent clients without giving raw database credentials.

What data sources can Pylar connect to?

Pylar connects to major data warehouses and databases including Snowflake, Google BigQuery, PostgreSQL, MySQL, Amazon Redshift, MotherDuck, and Supabase. It also supports business applications and SaaS platforms such as HubSpot, Salesforce, and Google Sheets.

Which MCP clients work with Pylar?

Pylar publishes tools that integrate with any MCP-compatible environment. Supported agent builders and interfaces include Claude Desktop, Cursor, LangGraph, Zapier, Make, and n8n.

Do AI agents get direct access to databases in Pylar?

No. Pylar uses governed SQL views as the sole access layer. AI agents only interact with the views and tools you explicitly define, preventing raw database access and shielding sensitive underlying records.