"Help with cryptocurrency flashloan arbitrage strategies" matching MCP servers:

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

An MCP server that integrates with mem0.ai to help users store, retrieve, and search coding preferences for more consistent programming practices.

Enables AI assistants to consult other AI models via OpenRouter for help with coding tasks.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

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.

Provides AI coding agents with access to CleanSlice architecture documentation, rules, and conventions. It enables users to search documentation and retrieve essential patterns to help AI build applications correctly.

AI task planner for coding assistants that breaks goals into ordered steps, verifies each step with isolated test runs, learns from failures, and saves successful strategies as reusable recipes.

A unified hub for centrally managing and dynamically orchestrating multiple MCP servers/APIs into separate endpoints with flexible routing strategies.

Enables MCP-compatible coding agents to run the local Antigravity CLI as a coding agent, manage conversation context and common options, and inspect usage, quota, models, version, help, and read-only slash commands.

An AI-powered developer assistant MCP server that provides filesystem tools (list_files, read_file, search_files, write_file) to help AI agents inspect, analyze, and modify real codebases via the Model Context Protocol.

The AI-native Rust backend framework + generation platform. Help agents design, generate, verify and package complete backends.

dev-brain-mcp

Provides Cursor-like code intelligence using tools like ripgrep, ctags, and tree-sitter to help LLMs explore and understand entire codebases. It implements a structured, phase-gated workflow to ensure high-confidence code modifications and eliminate hallucinations.

Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.

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 delegating coding tasks to isolated Claude Code subprocesses billed against a GLM Coding Plan, with tools to delegate, await, continue, list, cancel, and inspect runs.

Provides TypeScript and JavaScript code refactoring operations using ts-morph, allowing AST-based symbol renaming, file/folder renaming, reference searching, and path alias removal when integrated with editor extensions like Cursor.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

Scoped, low-latency persistent memory layer for AI agents, Cursor, and Claude Code over Model Context Protocol with sub-50ms hybrid search.