"Using Logseq data as context for chat applications" matching MCP servers:

Multi-cloud MCP server that exposes cloud AI models as tools for AI CLI agents, supporting streaming, conversation history, parallel multi-model queries, and dynamic model discovery.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

A remote MCP server for Google Chat, deployed on Cloudflare Workers without authentication, enabling tool execution via MCP protocol.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

Generates and deploys Cloudera Data Engineering (CDE) Airflow jobs from ODCS data contracts, validating live table data in CDW against schema and data-quality rules without WAP staging.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Provides a modular MCP server to integrate with IBM Data Intelligence services, enabling secure interaction with data intelligence capabilities via tools and skills.

Provides secure integration between MCP clients and IBM Data Intelligence services, enabling AI assistants to interact with IBM's data intelligence capabilities for data management and analytics operations.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Provides AI agents with secure, natural-language access to Oracle Cloud Infrastructure through 69 tools covering services like compute, storage, networking, and databases. It features deep IAM integration and supports deployment across platforms like Claude Desktop, Cursor, and OCI Generative AI.

Enables natural language-powered ETL workflows using Airflow, AWS Glue, Athena, and S3, allowing LLM agents to control and monitor data infrastructure.

Enables AI agents to analyze BigQuery datasets through MCP, using tools to inspect datasets and execute read-only SQL queries.

This MCP server enables users to interact with AWS Amplify Gen2 application data through natural language, allowing AI assistants like Claude to perform operations on Amplify data models using conversational language instead of complex code.

Enables interaction with AWS Amplify Gen2 application data through natural language, allowing AI assistants to query, create, update, and delete records using conversational commands with Cognito authentication.

MCP FOR ITSM TOOL INTEGRATION

This read-only MCP Server allows you to connect to Azure Data Lake Storage data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI agents to query Microsoft Entra data using natural language, converting requests into Microsoft Graph API calls for read-only enterprise IT scenarios.