"Telegram MCP Server by DLHellMe" matching MCP servers:

Record Python/Rust/TypeScript program runs to local SQLite; query call trees, exceptions, and value flow over MCP — refuses rather than guesses. Not the unrelated Telegram sensorium-mcp.

MCP server for the hy-app component library, enabling AI editors to search components, retrieve APIs and examples, check platform support, access hooks and tools, and validate component usage.

Enables AI clients such as Claude, Cursor, Cline, and Codex to remotely drive IDA Pro over HTTP through 88 tools, covering Hex-Rays decompilation, disassembly, cross-reference tracing, type and struct reconstruction, C header import, memory reading and patching, and full dynamic debugging with breakpoints, registers, and stepping.

Read, inspect and navigate codebase symbols by connecting to a Language Server

A local MCP server that turns AI clients into power users of local git repositories, enabling clone, browse, search, and inspect code without burning API tokens.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables AI coding agents to efficiently navigate and understand large codebases by providing tools for entry point location, call chain analysis, and impact assessment, reducing context consumption and model costs.

Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.

Enables LLMs to efficiently navigate and analyze large diff files by providing pattern-based chunk navigation, allowing direct access to relevant changes without loading entire diffs into context.

Indexes codebases cut at function and class boundaries into Oracle AI Database 26ai, letting AI coding tools search code by name or meaning, trace callers, callees and change impact, read per-module wiki pages, and recall facts from earlier sessions. All of it is served over the Model Context Protocol with embeddings computed in-database, so no source code leaves the machine and no API key is required.

Serves token-efficient code context for AI coding assistants by exposing Python signatures, call graphs, and budget-packed task context as MCP tools, enabling precise codebase queries without reading entire files.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

Enables static security audit of Solidity smart contracts by analyzing source code or deployed bytecode for vulnerabilities, providing risk scores and detailed findings.

Static scanner for MCP/agent-gateway readiness anti-patterns, providing a 7-dimension R/Y/G score by scanning code and config for common failure modes.

Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

MCP server that exposes pre-extracted facts about code behavior, design decisions, and assumptions to AI agents, saving time and tokens by avoiding direct source file reading.

An MCP server for SonarQube that enables LLM agents to discover projects, analyze code quality metrics, check Quality Gate status, search issues with filters, and rank projects by worst-performing metrics. It provides read-only, safe access to SonarQube instances with structured outputs and error handling.

AI-powered QA testing platform — catches JS errors, accessibility failures, visual regressions, API loops, security issues, and more via Chrome DevTools MCP