"Data Crawling Techniques and Tools for Financial Data" matching MCP servers:

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.

Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.

Exposes portfolio allocation, concentration risk, retirement projections, RAG document search, and a full multi-agent financial advisor query as MCP tools for use from Claude Code.

Enables local data discovery by indexing metadata from SQLite, CSV, and Markdown sources, providing hybrid keyword and TF-IDF semantic search via MCP tools (listSources, indexSource, search, getSchema) and a REST API.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables multi-agent financial research through MCP, combining live or offline market, news, fundamentals, document RAG, and risk tools with critic review, synthesis, and execution tracing.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Salesforce Data Cloud (beta): https://www.cdata.com/download/download.aspx?sku=LRZK-V&type=beta

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta

Provides tools for RAG-based financial document retrieval, financial calculations, Yahoo Finance stock data, and portfolio analysis via JSON-RPC 2.0 protocol.

Secure Edge Gateway for Data Normalization.

Enables LLMs and AI agents to access real-time web data, search websites, and navigate the web without getting blocked. Includes 5,000 free monthly requests and supports web scraping, browser automation, and bypassing geo-restrictions.

Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.