perplexity-control-mcp
Comprehensive MCP server providing full programmatic control over the Perplexity API, including agent, sonar, search, embeddings, key management, and cost estimation tools.
README
@garza-os/perplexity-control-mcp
A comprehensive MCP (Model Context Protocol) server that provides full programmatic control over the Perplexity API platform. Unlike the official Perplexity MCP server (which only exposes search, ask, research, and reason), this server is a complete control plane.
Why this exists
The official Perplexity MCP server wraps only the Sonar chat endpoint and hides the underlying API. This server exposes every Perplexity API surface:
| Capability | Official MCP | This server |
|---|---|---|
| Sonar chat completions | ✅ (as ask) |
✅ sonar_chat |
| Deep research | ✅ (as research) |
✅ sonar_chat + sonar_async_* |
| Agent API | ❌ | ✅ agent_create |
| Raw web search | ❌ | ✅ web_search |
| Async jobs | ❌ | ✅ sonar_async_submit/get/list |
| Embeddings | ❌ | ✅ embeddings_create |
| Contextualized embeddings | ❌ | ✅ embeddings_contextualized |
| API key management | ❌ | ✅ api_key_generate/revoke/rotate |
| Cost estimation | ❌ | ✅ estimate_cost |
| Model catalog | ❌ | ✅ list_models |
| Health check | ❌ | ✅ health_check |
| HTTP transport | ❌ | ✅ Streamable HTTP |
| Full parameter control | ❌ | ✅ All API params exposed |
Installation
git clone <repo>
cd perplexity-control-mcp
npm install
cp .env.example .env
# Edit .env and set PERPLEXITY_API_KEY
npm run build
Configuration
| Variable | Default | Description |
|---|---|---|
PERPLEXITY_API_KEY |
(required) | Your Perplexity API key |
MCP_TRANSPORT |
stdio |
stdio or http |
MCP_PORT |
3001 |
HTTP port (only for http transport) |
MCP Client Configuration
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"perplexity-control": {
"command": "node",
"args": ["/absolute/path/to/perplexity-control-mcp/dist/index.js"],
"env": {
"PERPLEXITY_API_KEY": "pplx-your-key-here"
}
}
}
}
Cursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"perplexity-control": {
"command": "node",
"args": ["/absolute/path/to/perplexity-control-mcp/dist/index.js"],
"env": {
"PERPLEXITY_API_KEY": "pplx-your-key-here"
}
}
}
}
Comet (HTTP transport)
Start the server in HTTP mode:
MCP_TRANSPORT=http MCP_PORT=3001 PERPLEXITY_API_KEY=pplx-... npm start
Then configure Comet to use http://localhost:3001/mcp.
npx (without cloning)
After publishing to npm:
{
"mcpServers": {
"perplexity-control": {
"command": "npx",
"args": ["-y", "@garza-os/perplexity-control-mcp"],
"env": {
"PERPLEXITY_API_KEY": "pplx-your-key-here"
}
}
}
}
All Tools
Agent API
agent_create
Create an agent response using the Perplexity Agent API (POST /v1/agent). Supports multi-step agentic reasoning with tool use.
| Parameter | Type | Required | Description |
|---|---|---|---|
input |
string | message[] | ✅ | User input (string or messages array) |
model |
string | * | Provider/model format, e.g. openai/gpt-5.4 |
models |
string[] | * | Fallback model chain (max 5). Overrides model |
preset |
enum | * | fast-search, pro-search, deep-research, advanced-deep-research |
instructions |
string | System instructions | |
tools |
array | web_search, fetch_url, or function tools |
|
max_output_tokens |
integer | Maximum response tokens | |
max_steps |
integer (1-10) | Maximum agentic steps | |
reasoning |
object | `{effort: "low" | |
response_format |
object | Structured output: {type: "json_object"} etc |
|
language_preference |
string | ISO 639-1 code, e.g. "en" |
*One of model, models, or preset is required.
Sonar API
sonar_chat
Chat completions with live web grounding (POST /v1/sonar).
| Parameter | Type | Description |
|---|---|---|
model |
enum | sonar, sonar-pro, sonar-reasoning, sonar-reasoning-pro, sonar-deep-research |
messages |
message[] | Conversation messages with role and content |
max_tokens |
integer | Max response tokens |
temperature |
float (0-2) | Sampling temperature |
top_p |
float (0-1) | Nucleus sampling probability |
search_domain_filter |
string[] | Whitelist/blacklist domains (prefix - to exclude) |
search_recency_filter |
enum | day, week, month, year |
return_images |
boolean | Include image results |
search_after_date_filter |
string | ISO 8601 date |
search_before_date_filter |
string | ISO 8601 date |
user_location |
object | {country, city, region, timezone} |
search_language_filter |
string | BCP 47 language tag |
sonar_async_submit
Submit an async deep research job (POST /v1/async/sonar). Same parameters as sonar_chat. Returns a request_id.
sonar_async_get
Poll an async job (GET /v1/async/sonar/{request_id}).
| Parameter | Type | Description |
|---|---|---|
request_id |
string | ID from sonar_async_submit |
sonar_async_list
List all async jobs (GET /v1/async/sonar). No parameters.
Search API
web_search
Raw web search returning full page content (POST /search).
| Parameter | Type | Description |
|---|---|---|
query |
string | string[] | Query or up to 5 queries |
max_results |
integer (1-20) | Results per query (default 5) |
max_tokens |
integer (≤1M) | Total token budget |
max_tokens_per_page |
integer | Per-page token limit (default 4096) |
search_domain_filter |
string[] (≤20) | Domain include/exclude list |
search_language_filter |
string[] (≤10) | BCP 47 language filter |
search_recency_filter |
enum | day, week, month, year |
search_after_date_filter |
string | ISO 8601 date |
search_before_date_filter |
string | ISO 8601 date |
last_updated_after_filter |
string | ISO 8601 date |
last_updated_before_filter |
string | ISO 8601 date |
country |
string | ISO 3166-1 alpha-2 country code |
search_mode |
enum | academic or sec |
Embeddings API
embeddings_create
Generate dense vector embeddings (POST /v1/embeddings).
| Parameter | Type | Description |
|---|---|---|
input |
string | string[] | Text to embed |
model |
enum | pplx-embed-v1-0.6b, pplx-embed-v1-4b |
dimensions |
integer (128-2560) | Output vector dimensions |
encoding_format |
enum | base64_int8, base64_binary |
embeddings_contextualized
Document-aware embeddings where each chunk's vector is influenced by surrounding context (POST /v1/contextualizedembeddings).
| Parameter | Type | Description |
|---|---|---|
input |
string[][] | Array of documents, each being an array of chunks |
model |
enum | pplx-embed-context-v1-0.6b, pplx-embed-context-v1-4b |
dimensions |
integer (128-2560) | Output vector dimensions |
encoding_format |
enum | base64_int8, base64_binary |
API Key Management
api_key_generate
Generate a new API key (POST /generate_auth_token).
| Parameter | Type | Description |
|---|---|---|
token_name |
string | Optional label for the key |
Returns: { auth_token, created_at_epoch_seconds, token_name }
api_key_revoke
Revoke an API key (POST /revoke_auth_token). Irreversible.
| Parameter | Type | Description |
|---|---|---|
auth_token |
string | The key to revoke |
api_key_rotate
Convenience: generates a new key, tests it, then revokes the current key.
| Parameter | Type | Description |
|---|---|---|
token_name |
string | Optional label for the new key |
Returns: { new_key, old_key_revoked, note }
Save the new_key immediately and update PERPLEXITY_API_KEY in your environment.
Utility Tools
estimate_cost
Calculate estimated USD cost before sending a request.
| Parameter | Type | Description |
|---|---|---|
model |
string | Model ID |
input_tokens |
integer | Input token count |
output_tokens |
integer | Output token count |
tool_invocations |
object | {web_search: N, fetch_url: N} |
list_models
Returns the full model catalog with descriptions, context lengths, and pricing.
health_check
Verifies API connectivity and key validity. Makes a minimal test request and returns latency and rate limit information.
Architecture
perplexity-control-mcp/
├── src/
│ ├── index.ts # Entry point — stdio or HTTP transport
│ ├── config/
│ │ └── index.ts # Env var validation (Zod)
│ ├── services/
│ │ └── perplexity-client.ts # Centralized HTTP client
│ └── tools/
│ ├── index.ts # Tool registry + request routing
│ ├── agent-tools.ts # agent_create
│ ├── sonar-tools.ts # sonar_chat, sonar_async_*
│ ├── search-tools.ts # web_search
│ ├── embeddings-tools.ts # embeddings_create, embeddings_contextualized
│ ├── admin-tools.ts # api_key_generate/revoke/rotate
│ └── utility-tools.ts # estimate_cost, list_models, health_check
├── .env.example
├── package.json
└── tsconfig.json
Client features
- Automatic
Authorization: Bearertoken injection - Structured error responses with HTTP status codes
- Rate limit header parsing (
X-RateLimit-Remaining,X-RateLimit-Reset,X-RateLimit-Limit) - Automatic cost calculation from response
usageobjects - Request logging to stderr
Transport
- stdio (default): Pipe-based transport for local MCP clients
- http: Stateful Streamable HTTP transport with per-session server instances. Each session gets its own
Serverinstance. Sessions are cleaned up on disconnect.
Development
# Watch mode
npm run dev
# Build
npm run build
# Run (stdio)
PERPLEXITY_API_KEY=pplx-... npm start
# Run (HTTP)
MCP_TRANSPORT=http PERPLEXITY_API_KEY=pplx-... npm start
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.