How should deep-research-ai-agent be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Claim this agent

Agent DossierGITHUB OPENCLEWSafety 66/100

Xpersona Agent

deep-research-ai-agent

An intelligent multi-agent research system powered by CrewAI and Google Gemini that performs comprehensive web research, analyzes information, and generates professional reports. The system uses coordinated AI agents to deliver thorough, well-structured research outputs. 🤖 Deep Research AI Agent An intelligent **multi-agent** research system powered by **LangChain**. A ReAct **Research Agent** autonomously searches the web via **Firecrawl MCP**, then **Summarization** and **Presentation** agents produce a professional PDF report — using **Ollama** (default) or **Google Gemini**. ✨ Features - **Three-agent workflow** — Research (autonomous + tools) → Summarizer → Presenter ($1) - **R

OpenClaw · self-declared

Trust evidence available

View Source

git clone https://github.com/Naveen-1-1/deep-research-ai-agent.git

Overall rank

#36

Adoption

No public adoption signal

Trust

Unknown

Freshness

May 20, 2026

Freshness

Last checked May 20, 2026

Best For

deep-research-ai-agent is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Overview Evidence & Timeline Artifacts & Docs API & Reliability Media & Related Machine Appendix

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

No verified compatibility signals

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 20, 2026

Vendor

Naveen 1 1

Artifacts

Benchmarks

Last release

Unpublished

Install & run

Setup Snapshot

git clone https://github.com/Naveen-1-1/deep-research-ai-agent.git

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Naveen 1 1

profilemedium

Observed May 20, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed May 20, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Events

Release & Crawl Timeline

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredGITHUB OPENCLEW

Captured outputs

Artifacts Archive

Extracted files

Examples

Snippets

Languages

python

Executable Examples

text

User Query (Streamlit)
       ↓
Research Agent (ReAct) ──tool──► firecrawl_search → Firecrawl MCP (stdio)
       ↓
Summarization Agent (LCEL chain, no tools)
       ↓
Presentation Agent (LCEL chain, no tools)
       ↓
PDF + Streamlit preview

bash

git clone <your-repo-url>
cd deep-research-ai-agent

bash

python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate

bash

python -m pip install -r requirements.txt

bash

cp .env.example .env
# Edit .env — set LLM_PROVIDER, keys, and model names

env

LLM_PROVIDER=ollama
OLLAMA_MODEL=qwen3:8b
OLLAMA_BASE_URL=http://localhost:11434
FIRECRAWL_KEY=your-firecrawl-api-key-here
LOG_LEVEL=INFO

Editorial read

Docs & README

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Full README

🤖 Deep Research AI Agent

An intelligent multi-agent research system powered by LangChain. A ReAct Research Agent autonomously searches the web via Firecrawl MCP, then Summarization and Presentation agents produce a professional PDF report — using Ollama (default) or Google Gemini.

Deep Research AI Agent UI

✨ Features

Three-agent workflow — Research (autonomous + tools) → Summarizer → Presenter (services/langchain_pipeline.py)
ReAct research agent — decides when and how to call firecrawl_search (no fixed search script)
Single search tool — Firecrawl MCP only (services/firecrawl_mcp.py)
Single LLM provider — LLM_PROVIDER=ollama (default) or gemini (utils/llm_config.py)
Configurable research — breadth and depth as guidance in the research agent prompt
PDF reports — downloadable ReportLab output with source links
Log safety — API keys redacted in logs; LOG_LEVEL for terminal verbosity

🏗️ Architecture

User Query (Streamlit)
       ↓
Research Agent (ReAct) ──tool──► firecrawl_search → Firecrawl MCP (stdio)
       ↓
Summarization Agent (LCEL chain, no tools)
       ↓
Presentation Agent (LCEL chain, no tools)
       ↓
PDF + Streamlit preview

| Agent | Tools | Role | |-------|--------|------| | Research | firecrawl_search | Autonomous web research; chooses queries and follow-ups | | Summarization | None | Bullet summary from research notes | | Presentation | None | Final report (Introduction, Key Findings, Conclusion) |

Firecrawl MCP spawns npx -y firecrawl-mcp over stdio. Requires Node.js / npx and FIRECRAWL_KEY.

LLM provider (one only)

Set LLM_PROVIDER to ollama or gemini. All agents use the same model from utils/llm_config.py.

| LLM_PROVIDER | Required in .env | |----------------|-------------------| | ollama (default) | OLLAMA_MODEL, OLLAMA_BASE_URL, Ollama running locally | | gemini | GOOGLE_API_KEY, optional GEMINI_MODEL |

Copy .env.example to .env and configure one provider block.

📋 Prerequisites

Python 3.11–3.13
pip and a virtual environment
Firecrawl API key — always required
Node.js / npx — required to run firecrawl-mcp
Ollama — when LLM_PROVIDER=ollama
Google API key — when LLM_PROVIDER=gemini

🚀 Installation

Clone the repository

git clone <your-repo-url>
cd deep-research-ai-agent

Create and activate a virtual environment

python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate

Install dependencies

python -m pip install -r requirements.txt

Configure environment

cp .env.example .env
# Edit .env — set LLM_PROVIDER, keys, and model names

⚙️ Configuration

Ollama (default)

LLM_PROVIDER=ollama
OLLAMA_MODEL=qwen3:8b
OLLAMA_BASE_URL=http://localhost:11434
FIRECRAWL_KEY=your-firecrawl-api-key-here
LOG_LEVEL=INFO

Install Ollama and pull your model: ollama pull qwen3:8b

Gemini (optional)

LLM_PROVIDER=gemini
GOOGLE_API_KEY=your-google-api-key-here
GEMINI_MODEL=gemini-2.5-flash-lite
FIRECRAWL_KEY=your-firecrawl-api-key-here
LOG_LEVEL=INFO

Optional: NPX_PATH=/full/path/to/npx if npx is not on your PATH.

Getting API keys

Google AI (Gemini) — Google AI Studio

Firecrawl — firecrawl.dev → API settings

🎯 Usage

Start the app

streamlit run main.py

Opens at http://localhost:8501

Run a research job

Enter a research query
Set Search Breadth (1–10, default 3) and Search Depth (1–5, default 2)
Click Run Deep Research
Watch agent progress in the terminal (LOG_LEVEL=INFO)
Read the report, preview the PDF, and download

Breadth and depth guide the Research Agent’s prompt (approximate angles and follow-up levels); the agent chooses concrete searches.

📦 Project structure

deep-research-ai-agent/
├── main.py                      # Streamlit UI
├── controllers/
│   └── research_controller.py   # Orchestration, PDF assembly
├── services/
│   ├── langchain_pipeline.py    # ReAct research + summarize + present
│   └── firecrawl_mcp.py         # MCP client
├── models/
│   └── pdf_generator.py         # ReportLab PDF
├── utils/
│   ├── llm_config.py            # LLM_PROVIDER → LangChain ChatModel
│   ├── tool_names.py            # firecrawl_search constant
│   ├── url_extract.py           # URL collection from search JSON
│   ├── mcp_config.py            # find_npx()
│   ├── markdown_cleaner.py
│   └── log_sanitizer.py
├── assets/                      # UI screenshot (optional)
├── requirements.txt
├── .env.example
└── README.md

🛠️ Technology stack

| Category | Technology | |----------|------------| | Agents | LangChain create_agent (ReAct research agent) | | Chains | LangChain LCEL (summarize, present) | | UI | Streamlit | | Local LLM | Ollama via langchain-ollama | | Cloud LLM | Google Gemini via langchain-google-genai | | Web search | Firecrawl via MCP | | PDF | ReportLab |

🔍 How it works

Load config — .env → llm_config.py.
Research Agent — ReAct loop calls firecrawl_search until it finishes notes (recursion_limit scales with breadth × depth).
Summarization Agent — condenses research output into bullets.
Presentation Agent — writes the final markdown report.
Deliver — PDF + Streamlit preview with collected URLs.

🐛 Troubleshooting

No logs in terminal

Set LOG_LEVEL=INFO in .env and restart Streamlit.
Logs appear when you run a research job, not only at startup.

Research Agent empty output / tool-calling failures (Ollama)

Use a larger model (qwen3:8b) or LLM_PROVIDER=gemini.
Smaller models may fail to call tools reliably.

Firecrawl MCP requires npx

Install Node.js or set NPX_PATH in .env.

Incomplete report / missing URLs

Try Gemini or reduce breadth/depth for shorter runs.

📄 License

🙏 Acknowledgments

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Machine interfaces

Contract & API

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/snapshot"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/contract"

curl -s "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/trust"

Operational fit

Reliability & Benchmarks

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.

No benchmark suites or observed failure patterns are available.

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingGITHUB OPENCLEW

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T02:09:03.977Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Naveen 1 1",
    "category": "vendor",
    "href": "https://github.com/Naveen-1-1/deep-research-ai-agent",
    "sourceUrl": "https://github.com/Naveen-1-1/deep-research-ai-agent",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-20T06:51:40.939Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-20T06:51:40.939Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-naveen-1-1-deep-research-ai-agent/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  }
]

Overview

Executive Summary

Setup Snapshot

Evidence & Timeline

Evidence Ledger

Release & Crawl Timeline

Artifacts & Docs

Artifacts Archive

Docs & README

🤖 Deep Research AI Agent

✨ Features

🏗️ Architecture

LLM provider (one only)

📋 Prerequisites

🚀 Installation

⚙️ Configuration

Ollama (default)

Gemini (optional)

Getting API keys

🎯 Usage

Start the app

Run a research job

📦 Project structure

🛠️ Technology stack

🔍 How it works

🐛 Troubleshooting

📄 License

🙏 Acknowledgments

API & Reliability

Contract & API

Reliability & Benchmarks

Media & Related

Media & Demo

Related Agents

activepieces

cherry-studio

AionUi

CopilotKit

Machine Appendix