web-research

name

web-research

description

Use the Perplexity MCP for any task that needs fresh / external / web-authoritative information. Triggers on requests like "research X", "look up Y", "what's happening with Z", "fact-check this", "find recent news about...", "competitive analysis of...", "what are customers saying about...", "is this still true?", "ask Perplexity...", "deep research on...", "do a teardown of [company]", or any question that benefits from cited live-web answers rather than knowledge from training. Choose the right Perplexity tool — quick lookup → perplexity_search; synthesized answer → perplexity_ask; multi-step analysis → perplexity_reason (Pro); long-form report → perplexity_research (Pro); ASI / heavy computation → perplexity_compute (Pro/Max). When Pro tools are unavailable on a Free account, chain multiple perplexity_search calls and synthesize manually — the source-finding works at every tier.

Perplexity MCP — when and how to use it

Claude has a Perplexity MCP server installed that hits the live web (often through a logged-in Perplexity session), returns citations, and can run multi-step research. Use it whenever the user is asking about something that benefits from fresh data — current events, real customer reviews, recent product launches, today's pricing, who-acquired-whom news, this-quarter's funding rounds.

Don't use Perplexity for things Claude already knows reliably from training (general concepts, historical events, well-established facts). Don't use it for code, math, internal reasoning, or anything that doesn't need the open web.

Plan tiers (Free / Pro / Max)

The Perplexity MCP routes to different models depending on the user's plan tier. Some tools are completely gated. Plan-tier limits change; verify at https://www.perplexity.ai/pricing.

Capability	Free	Pro	Max
perplexity_search	✅	✅	✅
perplexity_ask	✅ (force model: "turbo")	✅	✅
perplexity_reason	❌	✅	✅
perplexity_research	❌	✅	✅
perplexity_compute (ASI / Computer mode)	❌	partial	✅
perplexity_models, perplexity_login, perplexity_doctor	✅	✅	✅
perplexity_retrieve, perplexity_get_research, perplexity_list_researches	✅	✅	✅
perplexity_export, perplexity_sync_cloud, perplexity_hydrate_cloud_entry	✅	✅	✅

If you don't know the user's tier, attempt the Pro tool. If it fails with requires an authenticated Pro account, fall back to the free-tier pattern (see below). Don't ask the user to upgrade.

Tool routing — pick the right tool for the task

User asks for…	Use this tool	Notes
Quick fact, "what's X?", "find me the URL of…"	perplexity_search	Fastest. Free-tier safe.
Synthesized answer, "ask Perplexity…", "summarize what people are saying"	perplexity_ask	Pass model: "turbo" if Free. Returns follow_up_context you can pass back for follow-up questions.
Multi-step reasoning, "compare X and Y", "reason through…"	perplexity_reason	Pro. Falls back to a chain of perplexity_search + manual synthesis on Free.
Long-form research, "do a teardown of…", "deep research on…"	perplexity_research	Pro. Same fallback.
ASI / heavy computation, "model the cost of…", code-style analysis	perplexity_compute	Pro/Max. No good fallback — say so to the user.
List models available on the user's account	perplexity_models	Useful for diagnostics.
Re-fetch a Perplexity thread by URL or ID	perplexity_retrieve	When the user pastes perplexity.ai/search/<id>.
Fetch a specific saved research result	perplexity_get_research	Pair with perplexity_list_researches to discover IDs.
List previously saved research threads	perplexity_list_researches	Useful when the user references past work.
Export a research result to markdown	perplexity_export	Good for delivering to the user as a file.
Sync local state with cloud (cross-device consistency)	perplexity_sync_cloud	Rarely needed in normal chat flows.
Re-pull a single cloud entry locally	perplexity_hydrate_cloud_entry	Edge case — only if the user explicitly mentions a cloud-only entry.
Diagnose Perplexity install issues	perplexity_doctor	Pass probe: true to also do a live search probe.
Trigger interactive login	perplexity_login	Returns instructions only — login is interactive (email + OTP) and must be done from CLI or extension dashboard.

Sources picker — pick deliberately

Search-style tools accept sources: ["web", "scholar", "social"].

• web (default) — general web search; use for nearly everything.
• scholar — academic / peer-reviewed; use when the user wants research evidence.
• social — Reddit, forums, social media; use for "what are customers actually saying" / sentiment.

Combinations are fine: ["web", "social"] is a great default for product or company research where you want both vendor pages and community discussion.

Free-tier fallback (Pro-tool error)

If perplexity_reason or perplexity_research returns requires an authenticated Pro account:

1. Don't give up.
2. Decompose the question into 4–6 focused sub-questions.
3. Run those as parallel perplexity_search calls (which work at every tier).
4. Synthesize the answer yourself using the URLs each search returned. Lead with the most material finding (acquisitions, leadership exits, big funding rounds, etc.) — those reframe everything else.
5. Cite specific URLs in the answer.

The free-tier turbo model produces shorter / more outline-style synthesis, but source-finding is identical at every tier. Free users can get equivalent depth — they just have to chain calls.

Patterns

Pattern: company / competitor teardown

Don't try to do this in one call. Run focused parallel searches:

search 1: "[Company] background — founders, founding year, HQ, funding rounds, valuation"
search 2: "[Company] product — what they sell, pricing model, native vs integrated, architecture"
search 3: "[Company] customer reviews — G2, Capterra, TrustRadius, Reddit praise and complaints"
search 4: "[Company] customer logos — named customers, target segment, industry concentration"
search 5: "[Company] vs [main competitor] — where they win, where they lose"
search 6: "[Company] recent news 2024-2026 — launches, acquisitions, leadership changes, layoffs"

Then synthesize. Lead with the most surprising / material finding. End with "what this means" tying findings to whatever the user is actually deciding.

Pattern: fact-check

Quote the specific claim as the search query, with sources: ["web"]. Inspect citations — if they confirm, cite them; if they contradict, lead with that. Don't hedge if the evidence is clear.

Pattern: customer sentiment / "what are people saying"

perplexity_search with sources: ["web", "social"]. Always include social for sentiment work — Reddit and forum discussion is where the actual user voice lives.

Pattern: current-events question

perplexity_search with sources: ["web"]. The MCP automatically uses fresh web indexes. Add a time window in the query ("recent", "this week", "2026") if relevant.

Pattern: user pasted a URL

If the user pastes a URL and asks about its content, prefer fetching directly when you have a fetch tool (e.g. WebFetch). Perplexity is for discovering URLs you didn't have, not for re-reading ones you did.

Pattern: follow-up questions on the same thread

Save the follow_up_context blob from a perplexity_ask response. Pass it back to perplexity_ask on the next call to continue the same conversation thread. This is more coherent than starting a new search every time.

Writing good Perplexity queries

• Be specific. "Subskribe customer feedback" returns generic CPQ chatter. "Subskribe customer reviews — G2, Capterra, Reddit, Trailblazer Community" returns actual review-platform results.
• Include the time window when freshness matters: "2024–2026", "recent news", "this quarter".
• Name the exact sources you want in the query body. Perplexity uses them as ranking hints.
• Ask for the output shape you want: "list named customers", "quote real reviews", "compare side-by-side".

Handling the response

Perplexity responses include:

• The synthesized answer text
• A numbered Sources list with URLs
• A Suggested follow-ups list (sometimes useful for deciding what to search next)
• A Full thread URL on perplexity.ai (good to share with the user as the canonical record)
• A follow_up_context JSON blob — pass back to perplexity_ask for follow-ups in the same thread

When relaying results to the user, always include the cited URLs — citations are the whole point of using Perplexity vs. answering from training. Lead with the answer, then cite.

Don't

• Don't burn searches on things Claude already knows reliably.
• Don't dump raw Perplexity output unfiltered. Synthesize. Cite specific URLs. Make a recommendation.
• Don't make up facts. If a search returns nothing useful, say so — better to admit uncertainty than to fabricate.
• Don't ask the user to upgrade to Pro. The free-tier fallback gets equivalent depth with more searches.