"Using another LLM for research purposes" matching MCP servers:

Enables AI assistants to query hundreds of models across OpenAI, Google, and OpenRouter, with model discovery, deep-research jobs, and image generation.

Enables coding and research agents to run paid, cited deep research on AI infrastructure, MCP, and security topics via remote MCP tools, with query-tied excerpt packs and uncited or failed calls billed at $0.

An MCP server that enables AI assistants to interact with self-hosted Planka boards through the Planka REST API. It allows users to list, search, create, and update projects, boards, and cards using natural language.

MCP server exposing ATLAS research capabilities: live tokenized stock market data, on-chain source-of-truth reads, and published research atlases. Connects to MCP clients over stdio with no API keys required for public testnet endpoints.

An MCP server that provides LLMs access to other LLMs

Enables evidence-grounded implementation research by searching GitHub, scoring candidate repositories, extracting source evidence, and generating planning artifacts like research and implementation checklists.

Token cost math for LLM API calls: current per-million-token rates for 69 models across 17 providers, with local arithmetic for estimates, comparisons and monthly budgets. Rates are verified and date-stamped.

An MCP server that detects duplicated research directions and probes blind spots before committing to a project, helping researchers avoid wasted effort.

Enables AI agents to perform deep web research by searching, fetching, chunking, retrieving, and synthesizing cited answers from exact source passages via a deep_research tool.

Provides a private set of high-level tools for web research, focused URL investigation, read-only GitHub research, and persistent semantic memory via a Streamable HTTP MCP gateway.

Provides real-time LLM pricing and availability data as an MCP server, enabling AI agents to make optimal model routing decisions at inference time with cited pricing sources.

MCP server that completes prompts with automatic provider fallback across OpenAI, Anthropic Claude, and Google Gemini. It is rate-limit aware, retries on transient failures, and provides a transparent attempt log.

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

A unified MCP server for academic paper discovery, citation exploration, and research intelligence workflows over multiple scientific knowledge sources.

A read-only FastMCP server for academic research that lets agents search papers, inspect metadata, follow citation graphs, generate BibTeX, and read full texts of open-access PDFs via semantic scholar, OpenAlex, arXiv, DBLP, and Crossref.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.

An MCP server exposing a registry of paper-backed quantitative trading methods plus a deterministic, no-LLM decision helper for reproducible trading research.

A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.

Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.

Provides comprehensive access to Roam Research's API functionality. This server enables AI assistants like Claude to interact with your Roam Research graph through a standardized interface.