"Analysis of Grafana Dashboards" matching MCP servers:

MCP server for full lifecycle of 1C binary files (CF/CFE/EPF/ERF) without EDT import: unpack to a temporary directory, read and edit code/forms/help, search, diff, repack, and cleanup. Enables code analysis, patching, and bytecode decompilation of protected modules via natural language.

A specialized server that provides advanced TypeScript code manipulation and analysis capabilities, enabling refactoring, navigation, diagnostics, and module analysis through Claude.

A TypeScript-aware MCP server that provides coding agents with repository discovery, code intelligence, and web project context for local codebases. It enables deep symbol navigation, diagnostic reporting, and structural analysis of monorepos without requiring full IDE integration.

Streamlines development workflows through AI-assisted codebase analysis, comprehensive planning, task breakdown with dependencies, and automated implementation verification. Enables systematic approach to complex development tasks like framework migrations and feature implementation.

An MCP server for managing, editing, and running Stata .do files, integrating with Claude Desktop to enable natural language control of Stata analysis on macOS.

MCP server that enables Claude Code to delegate tasks to DeepSeek and other LLMs, offering 20 tools for code review, analysis, testing, and code generation.

A tiny Hermes-friendly bridge that exposes oh-my-pi's CLI as MCP tools (prompt and doctor) for code generation and environment verification.

Specialized MCP server for coding workflows with web search and image analysis tools.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Provides C# coding agents with compiler-accurate symbol analysis, including references, renames, and impact analysis for .NET solutions.

Provides AI-powered development assistance with continuous chain-of-thought reasoning (CoConuT), automated task planning and execution, quality validation, and persistent memory of project context and decisions.

A Windows proof-of-concept MCP server that connects ChatGPT developer-mode to a local Codex CLI via Secure MCP Tunnel, exposing a small set of read-only, allowlisted tools in an isolated workspace.

Enables semantic code search across projects using AI embeddings to find code by meaning rather than just text matching. Provides fast intelligent search, symbol analysis, and code similarity detection with multi-language support.

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

This MCP server enables automated maintenance and code analysis for Python/pytest repositories in isolated Docker environments. It supports read-only investigations, fix-and-verify tasks, and provides full audit trails with SQLite event history and artifact exports.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Multi-agent AI system for code development with orchestration, architecture planning, code analysis, semantic knowledge search, and intelligent debugging capabilities powered by SurrealDB and Groq.

Enables coding agents to query real SF Symbol names from the local SF Symbols app on Mac, helping generate valid SwiftUI/UIKit code without guessing.

Enables AI assistants to work through complex problems step-by-step with dynamic thought processes, allowing for revision of previous steps, exploration of alternative approaches, and flexible planning as understanding deepens.