Consensus MCP lets AI assistants search 400+ million peer-reviewed research papers. Connect your preferred client below. You’ll be searching in under 2 minutes
DeepSeek Harness (DSH) is DeepSeek's agent harness. Each MCP server is one plugin entry in your project config.
This guide connects Consensus MCP to DeepSeek Harness through MewCP, so DeepSeek Harness can use Consensus MCP's 1 tool, like search, without your Consensus MCP credentials ever reaching the app.
Consensus MCP signs in through managed OAuth. MewCP stores the token encrypted, refreshes it before it expires and injects it only at call time. Your agent never holds it, so it can never leak it.
More apps
Crawl websites and extract clean structured data optimized for AI applications and automation. Collect content from the web at scale while maintaining high-quality outputs.
Extract structured data from websites and public web pages. Fetch content, parse information and transform online data into formats that can be consumed by applications, agents and workflows.
TinyFish MCP for running AI-driven browser automation tasks, deep web research, persistent browser login profiles, remote CDP browser sessions, and agentic wallet payments.
Scrape, extract, and understand the web, plus identify any company from a domain, email, name, or transaction string. This MCP server exposes Context.dev's API for web scraping in multiple formats (raw HTML, Markdown, screenshots, images, sitemaps, and web search), schema-driven structured data extraction, design-system extraction (styleguides and fonts), and brand intelligence lookups. It's built for AI agents that read, summarize, or monitor web content, for enriching CRM, KYC, or fintech pipelines with company and brand data, and for extracting a competitor's design system or structured product and pricing data at scale.
Other clients
Consensus MCP works the same way in every client below. Pick yours for its own guide.
Free to start.
Scope access to the exact Consensus MCP tools and accounts you allow, work and personal side by side. Anything outside that scope is refused at call time, even when the model asks for it.
Each call is logged: what ran, on which account, and whether it worked. Failures come back structured, so the agent knows whether to retry instead of guessing.
Every app sits behind one secure MCP URL, and there is no server for you to deploy or keep running. Add an integration in the dashboard and it is live on the next call, with no config to change and no new credentials to wire up. Tools load only when a task needs them, so your agent stays fast and focused however many apps you connect.
In your DSH project, or the patch file you mount plugins from.
One plugin instance is one MCP server. Add this to your plugin list.
Tools register as mcp__mewcp__<tool_name>. Sign in when the browser window opens.
Start a new chat and ask: "List the tools you can use from MewCP." You should see your connected apps.
Search over 220 million peer-reviewed academic papers. Use this tool when the user asks about research, studies, evidence, scientific findings, clinical trials, medical research, or academic literature. Covers Semantic Scholar, PubMed, Scopus, and ArXiv. Returns paper titles, authors, abstracts, citation counts, journal quality scores, and direct URLs to each paper. All filters are optional — only apply them when the user explicitly asks. Example query → filter mappings: - "what does the evidence say about metformin for longevity?" → query="metformin longevity mortality", medical_mode=True, exclude_preprints=True - "recent peer-reviewed RCTs on SGLT2 inhibitors for heart failure" → query="SGLT2 inhibitors heart failure outcomes", year_min=2022, exclude_preprints=True, study_types=["rct"] - "long-term studies of statin side effects (1+ year)" → query="statin adverse effects long-term", duration_min=365, medical_mode=True - "what is dark matter?" → query="dark matter" (no filters — general question) - "coffee and cognition, excluding top-tier Q1 journals" → query="coffee cognition", sjr_min=2
