Parallect MCP Server
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- FlicenseAqualityNot gradedmaintenanceEnables AI assistants to perform comprehensive research by searching Google, mining Reddit discussions, scraping web content with JS rendering, and synthesizing findings with citations into structured context.5165 npm3-
- FlicenseNot gradedqualityBmaintenanceEnables 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.-
- AlicenseAqualityDmaintenanceEnables AI agents to run research queries across multiple public sources (Hacker News, Reddit, GitHub, Brave Search) in parallel, returning normalized results.5MIT
- AlicenseNot gradedqualityNot gradedmaintenanceConnects AI assistants to the Maestro research framework to orchestrate multi-agent research missions, including planning, research, and writing phases. It enables users to launch research tasks, track real-time progress, and retrieve comprehensive structured reports and notes.-
- AlicenseAqualityCmaintenanceEnables AI agents to perform professional-grade deep research by aggregating real-time data from multiple sources, evaluating source credibility, and generating comprehensive reports.311Apache 2.0
- FlicenseBqualityDmaintenanceEnables AI assistants to perform real-time web and academic searches using Perplexity's Sonar API.2-
TDQS
Scored across 11 tools
Tools target distinct stages of the research lifecycle and the descriptions explicitly resolve the riskiest overlap (research creates a new thread vs follow_up continues an existing one; research_status vs get_results distinguish progress from output). The only mild overlap is usage (spend analytics) versus balance (credit balance), but both descriptions make the boundary clear.
All names are snake_case, but verb styles are mixed: some are verb_noun (get_results, list_threads, search_claims, get_claim_evidence), some are bare nouns (research, usage, balance), and one is noun_status (research_status). It remains readable, but the pattern is not predictable.
Eleven tools sit squarely in the well-scoped 3-15 range. Each tool maps to a distinct capability (submit, poll, retrieve, follow up, browse threads, inspect claims, list providers, view spend/balance) with no filler.
The surface covers the full research lifecycle: submission, status polling, result retrieval, follow-ups, thread history, claim/evidence inspection, provider listing, and usage/billing. Minor gaps exist (no explicit cancel-job or delete-thread operation), but agents can work around these.