"Information and Resources on Finance" matching MCP servers:

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.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

A FastMCP integration with Hyperskill that allows AI agents to explain programming topics and search for programming resources using Hyperskill's learning materials.

Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.

A zero-dependency MCP server that allows multiple coding agents to coordinate work on the same repository using file locks, task claims, and status messages.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

Enables running code generation, deterministic compiler validation, sandboxed tests, and contract checks entirely on local hardware, with autonomous self-healing loops and compact telemetry receipts for orchestrator models.

https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.

An MCP server that lets an AI coding agent delegate implementation work to the OpenCode CLI, choosing an explicit provider + model on every call.

Visual feedback for AI coding agents on Astro sites, providing live annotations with source file:line, CSS selector, Tailwind classes, and computed styles.

MCP server that lets multiple coding-agent sessions on the same machine discover each other and collaborate through a shared SQLite database.

A source-preserving MCP server for coding agents working on Hearts of Iron IV mods, combining focus tree, GUI, and map tools with transaction safety.

A tiny always-on server that coordinates multiple coding-agent sessions on one project (a 'show'), using a worker/director pattern with polling, leases, and SQLite state.

MCP server to provide Jira Tickets information to AI coding agents like Cursor