search

search is a skill for Claude Code from exa-labs/exa-mcp-server. It costs 55 tokens per session (3,170 once invoked), scanned A, original, MIT.

A deep-research skill that searches across sources and coordinates research tasks for complex questions. It is intended for lead generation, literature reviews, competitive analysis, and broad investigations.

In plain words
What is it for?
Use it to research a topic in depth, find many relevant sources, review academic literature, compare competitors, or identify potential leads.
Why use it?
It helps when one search is not enough and the information must be gathered and combined from multiple sources.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents; mentions Claude Code.

Part of the exa-mcp-server plugin — 2 skills, 1 MCP server shipped together

Good fit Use it to research a topic in depth, find many relevant sources, review academic literature, compare competitors, or identify potential leads.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/exa-labs/exa-mcp-server/search
About the project

Exa MCP Server connects AI agents to Exa, a service for searching the web, fetching webpage content, and carrying out multi-step research. MCP, or Model Context Protocol, lets compatible AI clients call these capabilities as tools. The catalogue skills, MCP server, and plugin provide ways for coding agents to use Exa for web research.

exa-labs/exa-mcp-server · 4,987 stars · on GitHub · exa.ai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add exa-labs/exa-mcp-server --skill search
Clone the repo
git clone --depth 1 https://github.com/exa-labs/exa-mcp-server

Made for: Claude Code.

Or install exa-mcp-server, the plugin that ships this one along with the rest of its 2 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for search

README.md
[![agentmods](https://agentmods.dev/badge/skills/exa-labs/exa-mcp-server/search.svg)](https://agentmods.dev/skills/exa-labs/exa-mcp-server/search)
Your own site
<a href="https://agentmods.dev/skills/exa-labs/exa-mcp-server/search"><img src="https://agentmods.dev/badge/skills/exa-labs/exa-mcp-server/search.svg" alt="Measured on agentmods" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,170 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high System Prompt Leakage · line 169
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.03170
Opus 5 $0.00028 $0.01585
Sonnet 5 $0.00011 $0.00634
Haiku 4.5 $0.00006 $0.00317

Measured 8d ago against content hash 0aacd119c70b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

  • search — 100% identical, 0 lines differ
  • exa-search — 95% identical, 2 lines differ
skills/search/SKILL.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Exa Research Orchestrator

You are the orchestrator. Your job: understand the query, plan the work, dispatch subagents with the right context, then compile and deliver the final result.

Prerequisites: Auth

Server: https://mcp.exa.ai/mcp.

  1. OAuth (recommended) — client opens auth.exa.ai, user signs in with Google / SSO / email, JWT is attached automatically. No key to copy.
  2. API key — if OAuth isn't available, get one at https://dashboard.exa.ai/api-keys and pass it via Authorization: Bearer …, ?exaApiKey=…, or EXA_API_KEY (local npm).
  3. Anonymous — works without setup but rate-limited.

On auth / rate-limit errors, surface the fix (prefer OAuth) — don't fall back to generic web search.

Date Calculation (Do This First)

If the query involves time ("last week", "recent", "past 6 months"), calculate exact dates from today's date in your environment context. Write out the calculation explicitly before doing anything else. Never eyeball dates or reuse dates from examples.

Step 1: Assess the Query

Read the user's query and determine two things:

How complex is this?

  • Extremely Simple (e.g. reading the contents of 1-2 pages): Handle it yourself. Read references/searching.md for query-writing guidance, run the searches, review and filter results, then respond directly. No subagents needed.
  • Moderate (when a fast or low-effort search is requested): Delegate to 1 subagent to keep your context window clean.
  • Advanced (clear topic, clear filters, a few parallel searches): Light subagent use. One round of parallel subagents, then compile.
  • Complex (cross-referencing across entity types, multi-hop chains, exhaustive coverage, semantic filtering): Full multi-pass with parallel subagents.

Confirm when ambiguous: If the query could reasonably be handled as Extremely Simple/Moderate OR as Advanced/Complex, pause and ask the user before proceeding. Present:

  1. Your interpretation of the query
  2. The two (or more) plausible complexity levels
  3. What each level would look like in practice (e.g., "I can do a quick 1-2 search lookup, or I can fan out across 3-4 subagents to get deeper coverage")
  4. Let the user choose

Read the full file on GitHub · 208 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 208 lines · 55 tokens per session scan A 0aacd119c70b

Subscribe to this mod's changes

search is a skill published in the GitHub repository exa-labs/exa-mcp-server (4,987 stars, last pushed 18d ago), licensed MIT. It adds 55 tokens to every session and 3,170 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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