Get answers to questions with citations by querying Perplexity AI through Claude Desktop for web-based research and information retrieval.
MIT
131,132 tools. Last updated 2026-05-07 19:31
"A platform utilizing perplexity concepts for information retrieval" matching MCP tools:
- Return classes, functions, and methods annotated with domain concepts and semantic roles from a file path. Understand file structure and implemented concepts without reading the file content.MIT
- Retrieve the machine architecture (e.g., x86_64, aarch64) as JSON. Use for platform-conditional logic in agent workflows.MIT
- Retrieve comprehensive details about a function or class: signature, parameters, callers, callees, and related domain concepts – without reading its source file. Ideal for understanding what a symbol does and its role in the codebase.MIT
- Visualize the semantic topology of your codebase to identify which directories concentrate domain concepts, including entity counts and density, for a quick understanding of codebase layout before detailed analysis.MIT
- Search Redis documentation and knowledge base to find information on concepts, data structures, features, and use cases including caching, session management, and semantic search.MIT
Matching MCP Servers
- AlicenseAqualityDmaintenanceadvance mcp server utilizing Perplexity, without the need for an API keyLast updated62991GPL 3.0
- AlicenseBqualityCmaintenanceA server facilitating web search functionality by utilizing Perplexity AI's API, designed to integrate with the Claude desktop client for enhanced search queries.Last updated1294MIT
Matching MCP Connectors
Enable AI assistants to perform web searches using Perplexity's Sonar Pro.
VaultCrux Platform — 60 tools: retrieval, proof, intel, economy, watch, org
- Look up a concept to find all variants, related concepts, naming conventions, function signatures, and file locations. Resolves questions like 'what is X', 'what does X mean', or 'where is X used'.MIT
- Search Chargebee product documentation for explanations of billing, payments, and subscription management concepts.MIT
- Retrieve detailed information about a social media post, including content, media attachments, schedule, and per-platform publishing status to verify successful publication or diagnose errors.
- Find how two concepts relate by querying their connections in the memory graph. Scoped by optional domain, returns existing relationships.MIT
- Stores a knowledge fragment with source and evidence tier metadata for future retrieval via semantic RAG queries.MIT
- Get instructions for a hands-on reference project to practice certification concepts. Specify a project ID or leave blank to see available projects.MIT
- Retrieve detailed information about a specific connected social media account, including platform, username, health status, and posting ability, using its account ID.
- Retrieve the compiled implementation spec for a blueprint, including agent count, platform, and included artifacts.
- Retrieve all devices connected to the ThinQ Connect platform, returning a list with device information.Apache 2.0
- Assemble minimal token-efficient context for any concept, entity, or file by combining function body, structural summary, domain concepts, and logic cluster into a compact text block for LLM prompt injection.MIT
- Compare domain ontology between two git revisions to reveal added, removed, or changed concepts. Tracks vocabulary evolution across commits and helps identify naming inconsistencies in pull requests.MIT
- Retrieve the governing rules for all agents on the Lorg platform to understand platform governance and agent requirements.MIT
- Create a comparison slide in PowerPoint presentations to contrast two concepts with structured titles and content. Define left and right side details to highlight differences effectively.MIT
- Retrieve current operating system details and permitted file paths to enable cross-platform filesystem operations with proper platform-specific adaptations.