A
licenseB
qualityF
maintenanceA server facilitating web search functionality by utilizing Perplexity AI's API, designed to integrate with the Claude desktop client for enhanced search queries.
1
308
MIT
Perplexity MCP Server
by jaacob
The Perplexity MCP Server enables web search capabilities via Perplexity's AI API. With this server, you can:
Perform web searches by sending queries to Perplexity's API
Integrate with Claude Desktop App for seamless search functionality
Configure which Perplexity AI model to use (e.g., sonar-reasoning-pro, sonar) for different response capabilities
Automate search tasks by issuing search commands
Enable direct searching from prompts when integrated with compatible clients
Provides web search capabilities using Perplexity's API, allowing Claude to search for information on the internet
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Perplexity MCP Serverwhat are the latest developments in quantum computing?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Perplexity MCP Server
An MCP server that provides web search capabilities using Perplexity's API.
Prerequisites
Node.js (v14 or higher)
A Perplexity API key (get one at https://www.perplexity.ai/settings/api)
Claude Desktop App
Related MCP server: Perplexity Web Search MCP Server
Installation
Installing via Smithery
To install Perplexity Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @jaacob/perplexity-mcp --client claudeManual Installation
Clone this repository:
git clone https://github.com/jaacob/perplexity-mcp cd perplexity-mcpInstall dependencies:
npm installBuild the server:
npm run build
Configuration
Get your Perplexity API key from https://www.perplexity.ai/settings/api
Add the server to Claude's config file at
~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"perplexity-server": {
"command": "node",
"args": [
"/absolute/path/to/perplexity-mcp/build/index.js"
],
"env": {
"PERPLEXITY_API_KEY": "your-api-key-here",
"PERPLEXITY_MODEL": "sonar"
}
}
}
}Replace /absolute/path/to with the actual path to where you cloned the repository.
Available Models
You can specify which model to use by setting the PERPLEXITY_MODEL environment variable. Available options:
sonar-reasoning-pro- Most capable model with enhanced reasoningsonar-reasoning- Enhanced reasoning capabilitiessonar-pro- Faster response timessonar- Default model (used if no model is specified)
For up-to-date model pricing and availability, visit: https://docs.perplexity.ai/guides/pricing
Usage
After configuring the server and restarting Claude, you can simply ask Claude to search for information. For example:
"What's the latest news about SpaceX?"
"Search for the best restaurants in Chicago"
"Find information about the history of jazz music"
Claude will automatically use the Perplexity search tool to find and return relevant information.
If for whatever reason it decides not to, you can force the issue by prepending your prompt with "Search the web".
Development
To modify the server:
Edit
src/index.tsRebuild with
npm run buildRestart Claude to load the changes
License
MIT
Available Tools
1 toolsearchC
Search the web using Perplexity AI
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Search the web' implies a read-only operation, it doesn't specify rate limits, authentication requirements, result format, pagination, or any other behavioral characteristics. The description is minimal and lacks important operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that directly states the tool's function. There's zero waste or unnecessary verbiage. It's appropriately sized for a simple search tool and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect, whether there are limitations on query types, how results are formatted, or any other operational details. The description leaves too many questions unanswered for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with the 'query' parameter clearly documented. The description doesn't add any additional parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search the web') and specifies the resource/context ('using Perplexity AI'), making the purpose immediately understandable. It's not a tautology and provides specific information about what the tool does. However, since there are no sibling tools mentioned, it cannot demonstrate differentiation from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or specific contexts where it's most appropriate. It simply states what the tool does without any usage context or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
search
TDQS
B3.1/5.0
Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools, making disambiguation perfect. The tool's purpose is clearly defined as web search using Perplexity AI, leaving no room for misselection.
Naming Consistency5/5
A single tool named 'search' follows a consistent and straightforward verb-based naming pattern. There are no other tools to compare against, so no inconsistency can exist in the naming scheme.
Tool Count2/5
One tool is too few for a server named 'Perplexity MCP Server', which implies broader capabilities beyond just search. A single tool feels thin and under-scoped for what might be expected from a Perplexity AI integration, such as additional operations like summarization or follow-up queries.
Completeness2/5
The tool surface is severely incomplete for a web search domain; it only offers a basic search function without any complementary tools for refining results, getting summaries, or handling related queries. This creates significant gaps that could lead to agent failures in complex tasks.
Maintenance
ActivityInactive
ResponsivenessSyncing
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Real-time web search, reasoning, and research through Perplexity's API
Enable AI assistants to perform web searches using Perplexity's Sonar Pro.
Provides AI assistants with access to Seltz's powerful Web Search capabilities.
Web search, news, page retrieval, sitemaps, and trending topics through Search1API.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceAllows Claude or other MCP-compatible AI assistants to search the web and get up-to-date information using the Perplexity API, with features for filtering results by time period.8-
- AlicenseNot gradedqualityDmaintenanceIntegrates the Sonar API to provide Claude with real-time web-wide research capabilities. Enables conversational web searches through Perplexity's AI-powered search engine for up-to-date information retrieval.1,826MIT
- AlicenseNot gradedqualityDmaintenanceExposes Perplexity AI's search capabilities to Claude, enabling real-time web search and information retrieval within the assistant. The project is currently in active development with plans to support Perplexity Spaces and multi-source data synthesis.Apache 2.0
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