| name | perplexity-research |
| description | Live web research through Perplexity's closed synthesis engine — structured web results, deep multi-step investigations with reasoning, and quick sonar answers. Use when you need authoritative primary sources (gov/academic), academic citation discovery, or UK ecology/policy lookups; reach for it as the secondary engine after ceramic-search, or alongside it for important queries. |
Perplexity Research
Perplexity is a closed engine that returns a synthesized answer. Authoritative
primary sources (gov, academic) rank higher than keyword search, and the
academic/policy domain filters are tuned — but you don't control which sites are
searched and citations aren't independently verifiable.
Native MCP tools also available. When PERPLEXITY_API_KEY is set at boot, the
official @perplexity-ai/mcp-server is registered in .mcp.json and exposes four
direct Claude Code tools: perplexity_search, perplexity_ask, perplexity_research,
and perplexity_reason. Use those for quick one-shot queries. Use this skill when you
need the richer three-API surface: structured /search with domain/date filters,
/v1/agent deep research with multi-step reasoning, or Chat Completions for sonar
model variants.
Where this sits (secondary engine)
1. ceramic-search — default for web search. Keyword, fast, rich 8k extracts
2. perplexity-research — (this) Authoritative sources, academic/policy filters, synthesized
3. Claude WebSearch — tertiary fallback. Built-in, no API key
★ Complex/important? — run all three in parallel, dedupe + cross-verify
ceramic-search — primary. High-recall keyword search with dense page extracts.
perplexity-research (this) — secondary. Synthesized answers, authoritative source ranking.
web-researcher — you pick the engine + restrict to trusted-domain lenses, read
full sources, and verify every citation (verify_citation, citation_graph,
audit_bibliography). Use when your reputation is attached to the result.
deep-research — multi-agent harness (fan-out + adversarial verify + cited report)
that can call any of the above as its search backend.
When to use
- Live web search with structured results (title, URL, snippet, dates)
- Academic citation discovery (domain-filtered to scholar/pubmed/springer/nature)
- UK ecology and policy research (gov.uk, Natural England, JNCC, BTO)
- Deep multi-step research with reasoning and web search tools (Agent API)
- Quick factual queries with sonar models (Chat Completions, legacy)
When not to use
- Known URLs needing expansion → use
gemini-url-context
- YouTube transcript summarisation → use
web-summary
- Interactive browser automation → use
browser or playwright
- arXiv/PubMed/IEEE structured metadata search → use
web-researcher (academic_search)
- Patent search → use
web-researcher (patent_search)
- Multi-agent research with provenance verification → use
deep-research
- Experiment optimisation loops → use
autoresearch
Quick path
Fastest route for most needs is the native MCP perplexity_search /
perplexity_research tools. Drop to the raw three-API client when you need
domain/date filters, agent presets, or sonar model selection. Minimal /search call:
import os, requests
def search(query, max_results=10, country="GB", domain_filter=None):
payload = {"query": query, "max_results": min(max_results, 20), "country": country}
if domain_filter:
payload["search_domain_filter"] = domain_filter[:20]
resp = requests.post("https://api.perplexity.ai/search",
headers={"Authorization": f"Bearer {os.environ['PERPLEXITY_API_KEY']}",
"Content-Type": "application/json"},
json=payload, timeout=60)
resp.raise_for_status()
return resp.json().get("results", [])
Full three-API surface — parameter tables, the /v1/agent deep-research client,
Chat Completions + sonar models, domain-filter presets (academic, UK ecology),
academic-citation-mining and BNG cookbooks, and retry/error handling:
see references/api-surface.md.
Related skills
| Need | Skill |
|---|
| Structured academic metadata (DOI, authors) | web-researcher (academic_search) |
| Patent search | web-researcher (patent_search) |
| Multi-agent research with provenance | deep-research |
| URL content expansion | gemini-url-context |
| Experiment optimisation loops | autoresearch |
| Ontology enrichment with Perplexity | ontology-enrich |