"Resources or tools for conducting in-depth research" matching MCP servers:

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Research methods, workflow tools, and independent review for AI agents, packaged as a Skill, plugin, and local MCP server.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables deep research tasks using a multi-agent architecture that integrates any LLM and MCP tools. Available via MCP stdio, streamable HTTP, and SSE transports.

Orchestrates distributed research drones on Google Cloud Run, enabling scalable and bidirectional research task management.

Provides Dify apps with a secure, app-scoped MCP tool catalog and action gateway for authorized FlowFlox operations, enabling intent-driven planning and fixed operational processes without exposing global credentials.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

Enables AI agents to perform professional-grade deep research by aggregating real-time data from multiple sources, evaluating source credibility, and generating comprehensive reports.

Aggregates and routes multiple MCP servers with intelligent tool recommendation and batch parallel execution, enabling unified access and efficient tool usage.

An MCP server that exposes 43 domain tools behind 4 meta-tools, applying guardrails such as budgets, rate limits, schema validation, human-in-the-loop confirmation for mutations, PII redaction, and an append-only audit log while reducing context window usage.

A small local MCP adapter that lets Claude Code delegate bounded research work to Codex plan credits without giving the worker ownership of the final report.

Enables coding agents to perform web research by using TypeSafe JEV to semantically filter search results and parsed content blocks, returning compact evidence with provenance instead of dumping raw pages into the downstream model context.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables ChatGPT to invoke native OpenClaw browser operations directly through an MCP connection, forwarding actions to the local Gateway while preserving runtime errors and providing a local call monitor.

Persistence, headed Chromium browser control for MCP clients like OpenCode and Claude Code, enabling navigation, inspection, clicking, filling, and human-gated actions on JavaScript-heavy or login-walled pages.

A passive MCP server that exposes a toolbox of executable tools (shell, network, HTTP, AI search, SSH, S3 file operations) to autonomous agents via Streamable HTTP, with strong security features including Docker sandboxing and WAF.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

Enables Codex and other agents to discover live AutoDL GPU stock, produce cost- and time-optimized rental plans with human review, and manage approved Elastic/Pro deployments through the official API.

Transforms any API into an intelligent MCP agent in seconds, enabling natural language interaction with APIs through the Model Context Protocol.

Enables Claude Desktop to run Perplexity web searches and deep research that survive the client's tool-call timeout, using background jobs whose results are collected later. Answers include numbered sources and the real cost of each query.

An MCP (Model Context Protocol) server implementation using HTTP SSE (Server-Sent Events) connections with built-in utility tools including echo, time, calculator, and weather query functionality.

A multi-model research agent platform supporting Claude, Gemini, and OpenAI models with web search capabilities, thinking-enabled features, and citation support for advanced research workflows.

Enables AI-powered research by breaking a topic into subtopics, gathering information via agents, and compiling a report. Integrates with LangGraph and RAG for orchestration and contextual retrieval.

A Python-based MCP server that provides coordinate conversion between latitude/longitude and UTM/TWD97, along with various civil engineering calculation tools for LLM and AI application integration.

Sub-15ms edge intelligence tools for Claude Desktop, Cursor, and LLM agent loops. Provides sub-millisecond LLM JSON repair, web-to-markdown token compression (cuts context tokens up to 90%), PII redaction, and RFC 5322 B2B email deliverability verification at zero marginal token cost.

Enables web ChatGPT to drive durable, sandboxed Claude Code sessions on a local Mac, with controlled read, modify, verify, and recover operations via six session control tools.

A production-grade MCP server that provides a centralized microservice toolkit for LLM agents, enabling web search and extensible tool integration.

A meta-MCP server that orchestrates tools from multiple MCP servers, enabling complex Python workflows with loops and conditionals.