MCP Perplexity Search

Instructions

Implementation Reference

• src/index.ts:173-297 (handler)

  Request handler for CallToolRequestSchema that dispatches to chat_completion implementation, which calls Perplexity API with prompt templates and parameters.
  this.server.setRequestHandler( CallToolRequestSchema, async (request) => { if (request.params.name !== 'chat_completion') { throw new McpError( ErrorCode.MethodNotFound, `Unknown tool: ${request.params.name}`, ); } const { messages, prompt_template, custom_template, model = 'sonar', temperature = 0.7, max_tokens = 1024, format: user_format, include_sources: user_include_sources, } = request.params.arguments as { messages: Array<{ role: string; content: string }>; prompt_template?: PromptTemplate; custom_template?: CustomPromptTemplate; model?: string; temperature?: number; max_tokens?: number; format?: 'text' | 'markdown' | 'json'; include_sources?: boolean; }; // Apply template if provided (custom template takes precedence) const template = custom_template ?? (prompt_template ? PROMPT_TEMPLATES[prompt_template] : null); const format = user_format ?? template?.format ?? 'text'; const include_sources = user_include_sources ?? template?.include_sources ?? false; // Merge template system message with user messages if template is provided const final_messages = template ? [ { role: 'system', content: template.system }, ...messages, ] : messages; try { const controller = new AbortController(); const timeoutId = setTimeout( () => controller.abort(), 30000, ); // 30 second timeout try { const response = await fetch( 'https://api.perplexity.ai/chat/completions', { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${PERPLEXITY_API_KEY}`, }, body: JSON.stringify({ model, messages: final_messages, temperature, max_tokens, format, include_sources, }), signal: controller.signal, }, ); if (!response.ok) { const errorData = await response .json() .catch(() => ({})); throw new McpError( ErrorCode.InternalError, `Perplexity API error: ${response.statusText}${ errorData.error ? ` - ${errorData.error}` : '' }`, ); } const data: PerplexityResponse = await response.json(); if (!data.choices?.[0]?.message) { throw new McpError( ErrorCode.InternalError, 'Invalid response format from Perplexity API', ); } return { content: [ { type: format === 'json' ? 'json' : 'text', text: data.choices[0].message.content, }, ], }; } finally { clearTimeout(timeoutId); } } catch (error) { return { content: [ { type: 'text', text: `Error generating completion: ${ error instanceof Error ? error.message : String(error) }`, }, ], isError: true, }; } }, );
• src/index.ts:69-167 (schema)

  Input schema definition for the chat_completion tool, including messages, prompt templates, model parameters, etc.
  inputSchema: { type: 'object', properties: { messages: { type: 'array', items: { type: 'object', required: ['role', 'content'], properties: { role: { type: 'string', enum: ['system', 'user', 'assistant'], }, content: { type: 'string', }, }, }, }, prompt_template: { type: 'string', enum: Object.keys(PROMPT_TEMPLATES), description: 'Predefined prompt template to use for common use cases. Available templates:\n' + Object.entries(PROMPT_TEMPLATES) .map( ([key, value]) => `- ${key}: ${value.description}`, ) .join('\n'), }, custom_template: { type: 'object', description: 'Custom prompt template. If provided, overrides prompt_template.', properties: { system: { type: 'string', description: "System message that sets the assistant's role and behavior", }, format: { type: 'string', enum: ['text', 'markdown', 'json'], description: 'Response format', }, include_sources: { type: 'boolean', description: 'Whether to include source URLs in responses', }, }, required: ['system'], }, format: { type: 'string', enum: ['text', 'markdown', 'json'], description: 'Response format. Use json for structured data, markdown for formatted text with code blocks. Overrides template format if provided.', default: 'text', }, include_sources: { type: 'boolean', description: 'Include source URLs in the response. Overrides template setting if provided.', default: false, }, model: { type: 'string', enum: [ 'sonar-pro', 'sonar', 'llama-3.1-sonar-small-128k-online', 'llama-3.1-sonar-large-128k-online', 'llama-3.1-sonar-huge-128k-online', ], description: 'Model to use for completion. Note: llama-3.1 models will be deprecated after 2/22/2025', default: 'sonar', }, temperature: { type: 'number', minimum: 0, maximum: 1, default: 0.7, description: 'Controls randomness in the output. Higher values (e.g. 0.8) make the output more random, while lower values (e.g. 0.2) make it more focused and deterministic.', }, max_tokens: { type: 'number', minimum: 1, maximum: 4096, default: 1024, description: 'The maximum number of tokens to generate in the response. One token is roughly 4 characters for English text.', }, }, required: ['messages'], },
• src/index.ts:65-169 (registration)

  Registration of the chat_completion tool in the ListToolsRequestSchema handler.
  { name: 'chat_completion', description: 'Generate chat completions using the Perplexity API', inputSchema: { type: 'object', properties: { messages: { type: 'array', items: { type: 'object', required: ['role', 'content'], properties: { role: { type: 'string', enum: ['system', 'user', 'assistant'], }, content: { type: 'string', }, }, }, }, prompt_template: { type: 'string', enum: Object.keys(PROMPT_TEMPLATES), description: 'Predefined prompt template to use for common use cases. Available templates:\n' + Object.entries(PROMPT_TEMPLATES) .map( ([key, value]) => `- ${key}: ${value.description}`, ) .join('\n'), }, custom_template: { type: 'object', description: 'Custom prompt template. If provided, overrides prompt_template.', properties: { system: { type: 'string', description: "System message that sets the assistant's role and behavior", }, format: { type: 'string', enum: ['text', 'markdown', 'json'], description: 'Response format', }, include_sources: { type: 'boolean', description: 'Whether to include source URLs in responses', }, }, required: ['system'], }, format: { type: 'string', enum: ['text', 'markdown', 'json'], description: 'Response format. Use json for structured data, markdown for formatted text with code blocks. Overrides template format if provided.', default: 'text', }, include_sources: { type: 'boolean', description: 'Include source URLs in the response. Overrides template setting if provided.', default: false, }, model: { type: 'string', enum: [ 'sonar-pro', 'sonar', 'llama-3.1-sonar-small-128k-online', 'llama-3.1-sonar-large-128k-online', 'llama-3.1-sonar-huge-128k-online', ], description: 'Model to use for completion. Note: llama-3.1 models will be deprecated after 2/22/2025', default: 'sonar', }, temperature: { type: 'number', minimum: 0, maximum: 1, default: 0.7, description: 'Controls randomness in the output. Higher values (e.g. 0.8) make the output more random, while lower values (e.g. 0.2) make it more focused and deterministic.', }, max_tokens: { type: 'number', minimum: 1, maximum: 4096, default: 1024, description: 'The maximum number of tokens to generate in the response. One token is roughly 4 characters for English text.', }, }, required: ['messages'], }, }, ],
• src/prompt-templates.ts:8-41 (helper)

  Predefined prompt templates referenced in chat_completion schema and used in handler for system messages and format settings.
  export const PROMPT_TEMPLATES = { technical_docs: { system: 'You are a technical documentation assistant. Provide clear, accurate, and well-structured information with code examples where relevant.', format: 'markdown' as const, include_sources: true, description: 'Technical documentation with code examples and source references', }, security_practices: { system: 'You are a security expert. Provide detailed security best practices, implementation guidelines, and potential vulnerability mitigations.', format: 'markdown' as const, include_sources: true, description: 'Security best practices and implementation guidelines with references', }, code_review: { system: 'You are a code review assistant. Analyze code for best practices, potential issues, and suggest improvements.', format: 'markdown' as const, include_sources: false, description: 'Code analysis focusing on best practices and improvements', }, api_docs: { system: 'You are an API documentation assistant. Provide clear explanations of API endpoints, parameters, and usage examples.', format: 'json' as const, include_sources: true, description: 'API documentation in structured JSON format with examples', }, } as const;