"Tool or method for reading files in a project easily" matching MCP servers:

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

A focused project memory system that provides knowledge graph capabilities and SQLite database operations for intelligent entity tracking and workflow management. It enables AI models to maintain persistent project context through 17 specialized tools, 10 resources, and 27 pre-built prompts.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

An MCP server for institutional quantitative intelligence, integrating Calera FinSec SEC auditing, ICX infinite context memory, level-2 order book analysis, SQL backtesting, and post-trade execution auditing with security safeguards.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Enables interaction with Plaid's financial data API to sync bank transactions and retrieve account balances with secure encrypted token storage.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Enables task management (create, list, update tasks with priority and status) using SQLite storage via MCP tools.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

Enables AI models to interact with MySQL databases through MCP protocol, supporting queries, table schema inspection, and data manipulation operations.

Enables task management through natural language: create tasks, list and filter them, and update their status. It uses SQLite for persistence and supports both local stdio and remote SSE transports.

The Materials Project MCP Server is server that provides programmatic access to the Materials Project database. It enables LLMs, to search, analyze, and retrieve up to date materials science data.

Enables searching GitHub repositories, fetching readable web page text, and querying a local book database through MCP tool calls.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

A collection of MCP servers for database management and Gmail integration, allowing AI agents to perform database queries and email operations.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Enables AI agents to safely interact with Supabase through read-only and gated-write tools, with bounded queries, allowlists, and explicit project targeting.

Enables project and task management through a lightweight SQLite database, allowing users to create projects, add categorized tasks, track status changes, and get project statistics through natural language commands.

Converts SQL queries between different database dialects using the sqlglot library to ensure cross-system compatibility. It allows users to list supported dialects and transpile SQL code from one syntax to another through the Model Context Protocol.

MCP server offering tools to add numbers and fetch GitHub repos, a resource for apartment rules, and a prompt to explain SQL queries.