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exa-search

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

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Precio sin confirmar★ 89 Estrellas de GitHubRegistro actualizado · 7 sept 2026agent-skill

Resumen

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Exa Search

Neural search for web content, code, companies, and people via the Exa MCP server.

When to Activate

User needs current web information or news
Searching for code examples, API docs, or technical references
Researching companies, competitors, or market players
Finding professional profiles or people in a domain
Running background research for any development task
User says "search for", "look up", "find", or "what's the latest on"

MCP Requirement

Exa MCP server must be configured. Add to ~/.codex.json:

"exa-web-search": {
  "command": "npx",
  "args": ["-y", "exa-mcp-server"],
  "env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}

Get an API key at exa.ai.

Core Tools

web_search_exa

General web search for current information, news, or facts.

web_search_exa(query: "latest AI developments 2026", numResults: 5)

Parameters:

Param	Type	Default	Notes
`query`	string	required	Search query
`numResults`	number	8	Number of results

web_search_advanced_exa

Filtered search with domain and date constraints.

web_search_advanced_exa(
  query: "React Server Components best practices",
  numResults: 5,
  includeDomains: ["github.com", "react.dev"],
  startPublishedDate: "2025-01-01"
)

Parameters:

Param	Type	Default	Notes
`query`	string	required	Search query
`numResults`	number	8	Number of results
`includeDomains`	string[]	none	Limit to specific domains
`excludeDomains`	string[]	none	Exclude specific domains
`startPublishedDate`	string	none	ISO date filter (start)
`endPublishedDate`	string	none	ISO date filter (end)

get_code_context_exa

Find code examples and documentation from GitHub, Stack Overflow, and docs sites.

get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)

Parameters:

Param	Type	Default	Notes
`query`	string	required	Code or API search query
`tokensNum`	number	5000	Content tokens (1000-50000)

company_research_exa

Research companies for business intelligence and news.

company_research_exa(companyName: "OpenAI", numResults: 5)

Parameters:

Param	Type	Default	Notes
`companyName`	string	required	Company name
`numResults`	number	5	Number of results

people_search_exa

Find professional profiles and bios.

people_search_exa(query: "AI safety researchers at OpenAI", numResults: 5)

crawling_exa

Extract full page content from a URL.

crawling_exa(url: "https://example.com/article", tokensNum: 5000)

Parameters:

Param	Type	Default	Notes
`url`	string	required	URL to extract
`tokensNum`	number	5000	Content tokens

deep_researcher_start / deep_researcher_check

Start an AI research agent that runs asynchronously.

# Start research
deep_researcher_start(query: "comprehensive analysis of AI code editors in 2026")

# Check status (returns results when complete)
deep_researcher_check(researchId: "<id from start>")

Usage Patterns

Quick Lookup

web_search_exa(query: "Node.js 22 new features", numResults: 3)

Code Research

get_code_context_exa(query: "Rust error handling patterns Result type", tokensNum: 3000)

Company Due Diligence

company_research_exa(companyName: "Vercel", numResults: 5)
web_search_advanced_exa(query: "Vercel funding valuation 2026", numResults: 3)

Technical Deep Dive

# Start async research
deep_researcher_start(query: "WebAssembly component model status and adoption")
# ... do other work ...
deep_researcher_check(researchId: "<id>")

Tips

Use web_search_exa for broad queries, web_search_advanced_exa for filtered results
Lower tokensNum (1000-2000) for focused code snippets, higher (5000+) for comprehensive context
Combine company_research_exa with web_search_advanced_exa for thorough company analysis
Use crawling_exa to get full content from specific URLs found in search results
deep_researcher_start is best for comprehensive topics that benefit from AI synthesis

deep-research — Full research workflow using firecrawl + exa together
market-research — Business-oriented research with decision frameworks

Ver fuente ↗

Metadatos del archivo

name: exa-search
description: Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

Ver texto original

---
name: exa-search
description: Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
---

# Exa Search

Neural search for web content, code, companies, and people via the Exa MCP server.

## When to Activate

- User needs current web information or news
- Searching for code examples, API docs, or technical references
- Researching companies, competitors, or market players
- Finding professional profiles or people in a domain
- Running background research for any development task
- User says "search for", "look up", "find", or "what's the latest on"

## MCP Requirement

Exa MCP server must be configured. Add to `~/.codex.json`:

```json
"exa-web-search": {
  "command": "npx",
  "args": ["-y", "exa-mcp-server"],
  "env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}
```

Get an API key at [exa.ai](https://exa.ai).

## Core Tools

### web_search_exa
General web search for current information, news, or facts.

```
web_search_exa(query: "latest AI developments 2026", numResults: 5)
```

**Parameters:**

| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Search query |
| `numResults` | number | 8 | Number of results |

### web_search_advanced_exa
Filtered search with domain and date constraints.

```
web_search_advanced_exa(
  query: "React Server Components best practices",
  numResults: 5,
  includeDomains: ["github.com", "react.dev"],
  startPublishedDate: "2025-01-01"
)
```

**Parameters:**

| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Search query |
| `numResults` | number | 8 | Number of results |
| `includeDomains` | string[] | none | Limit to specific domains |
| `excludeDomains` | string[] | none | Exclude specific domains |
| `startPublishedDate` | string | none | ISO date filter (start) |
| `endPublishedDate` | string | none | ISO date filter (end) |

### get_code_context_exa
Find code examples and documentation from GitHub, Stack Overflow, and docs sites.

```
get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)
```

**Parameters:**

| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `query` | string | required | Code or API search query |
| `tokensNum` | number | 5000 | Content tokens (1000-50000) |

### company_research_exa
Research companies for business intelligence and news.

```
company_research_exa(companyName: "OpenAI", numResults: 5)
```

**Parameters:**

| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `companyName` | string | required | Company name |
| `numResults` | number | 5 | Number of results |

### people_search_exa
Find professional profiles and bios.

```
people_search_exa(query: "AI safety researchers at OpenAI", numResults: 5)
```

### crawling_exa
Extract full page content from a URL.

```
crawling_exa(url: "https://example.com/article", tokensNum: 5000)
```

**Parameters:**

| Param | Type | Default | Notes |
|-------|------|---------|-------|
| `url` | string | required | URL to extract |
| `tokensNum` | number | 5000 | Content tokens |

### deep_researcher_start / deep_researcher_check
Start an AI research agent that runs asynchronously.

```
# Start research
deep_researcher_start(query: "comprehensive analysis of AI code editors in 2026")

# Check status (returns results when complete)
deep_researcher_check(researchId: "<id from start>")
```

## Usage Patterns

### Quick Lookup
```
web_search_exa(query: "Node.js 22 new features", numResults: 3)
```

### Code Research
```
get_code_context_exa(query: "Rust error handling patterns Result type", tokensNum: 3000)
```

### Company Due Diligence
```
company_research_exa(companyName: "Vercel", numResults: 5)
web_search_advanced_exa(query: "Vercel funding valuation 2026", numResults: 3)
```

### Technical Deep Dive
```
# Start async research
deep_researcher_start(query: "WebAssembly component model status and adoption")
# ... do other work ...
deep_researcher_check(researchId: "<id>")
```

## Tips

- Use `web_search_exa` for broad queries, `web_search_advanced_exa` for filtered results
- Lower `tokensNum` (1000-2000) for focused code snippets, higher (5000+) for comprehensive context
- Combine `company_research_exa` with `web_search_advanced_exa` for thorough company analysis
- Use `crawling_exa` to get full content from specific URLs found in search results
- `deep_researcher_start` is best for comprehensive topics that benefit from AI synthesis

## Related Skills

- `deep-research` — Full research workflow using firecrawl + exa together
- `market-research` — Business-oriented research with decision frameworks

Revisar el código fuente

Precio y costes de ejecución

Obtener el skill: Precio sin confirmar
Ejecutarlo: Requisitos sin confirmar. Consulta los costes del agente, API y servicios en la fuente.
Licencia: MIT
Precio sin confirmar: No hemos confirmado el precio. Los enlaces existentes al código y a la instalación siguen disponibles.

Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →

Fuente del skill registrada

La ruta de instrucciones está registrada. No implica pruebas de ejecución, seguridad ni compatibilidad.

Revisar antes de instalar: Evitar instalación automática

Licencia: MIT

Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
No explicit limitations or safety considerations are documented (e.g., API rate limits, cost implications, or potential for biased results).
The skill assumes the Exa MCP server is already configured; no troubleshooting or fallback guidance is provided if the server is unavailable.
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 89 GitHub stars
Stars/forks activity: 89 stars, 2 forks; issue activity unavailable in current metadata
Permission surface: secrets or environment access, shell or command execution

Abrir auditoría completa

Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.

Empieza con una tarea pequeña

1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente: mturac/everything-openai-codex
Licencia: MIT
Versión: 1.0.0
Último push de GitHub: 24 ago 2026
Registro actualizado: 7 sept 2026
Ruta de instrucciones: .agents/skills/exa-search/SKILL.md @ b5057da5f42e

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

63/100

Prometedor

Confianza

57/100

Do not auto-install

Auditoría

72/100

Requiere revisión

Abrir auditoría completa Ver informe de evaluación

Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
No explicit limitations or safety considerations are documented (e.g., API rate limits, cost implications, or potential for biased results).
The skill assumes the Exa MCP server is already configured; no troubleshooting or fallback guidance is provided if the server is unavailable.
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 89 GitHub stars
Stars/forks activity: 89 stars, 2 forks; issue activity unavailable in current metadata
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Resultados: —

Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.

Acceso para agentes

La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Abrir API de instalación Formato de texto LLM Abrir Manifest Plan de resolución automática

Más detalles

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  ],
  "agent_contract": {
    "task_input": "Use exa-search in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 65/100 Manual review",
      "Audit: 72/100 Needs review",
      "Safety: 32/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "mturac-exa-search (exa-search)",
      "install_command": "npx skills add mturac/everything-openai-codex --skill exa-search",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "mturac-exa-search",
      "task": "Use exa-search in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/mturac-exa-search",
    "api": "https://www.openagentskill.com/api/agent/skills/mturac-exa-search",
    "audit": "https://www.openagentskill.com/skills/mturac-exa-search/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=mturac-exa-search&task=Use%20exa-search%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20exa-search%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20exa-search%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/mturac-exa-search/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/mturac-exa-search"
  }
}

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Creador: mturac
Fuente: mturac/everything-openai-codex
Indexado por: Índice comunitario de OpenAgentSkill

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Resumen

Exa Search

When to Activate

MCP Requirement

Core Tools

web_search_exa

web_search_advanced_exa

get_code_context_exa

company_research_exa

people_search_exa

crawling_exa

deep_researcher_start / deep_researcher_check

Usage Patterns

Quick Lookup

Code Research

Company Due Diligence

Technical Deep Dive

Tips

Related Skills

Revisar el código fuente

Precio y costes de ejecución

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