About Ambitus AI Models
Ambitus AI Models is an MCP server published by Ambitus-Intelligence in the Developer Tools category: a TUI‑first Python package and multi‑agent market research engine that orchestrates validated data collection, analysis, and report synthesis into citation‑rich PDF reports.
The repository has 13 stars and 2 forks, with the last commit 11 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/Ambitus-Intelligence/ambitus-ai-modelsThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
ambitus-intelligence 🔍
Ambitus Intelligence is a TUI‑first Python package and multi‑agent market research engine that orchestrates validated data collection, analysis, and report synthesis into citation‑rich PDF reports.
Technical diagrams : Flowcharts
UML of Ambitus : Ambitus-AI
https://github.com/user-attachments/assets/0b6cd0a2-a02f-4ea1-8fdb-6f51012f2fad
This repository contains AI/ML models, experiments, and tools powering ambitus Intelligence's market research automation platform.
All exploratory work, prototypes, and notebooks are organized under /notebooks.
🚀 Overview
ambitus-ai-models is the core engine behind Ambitus Intelligence’s automated market research platform. It provides:
-
Orchestrated Multi‑Agent Workflows
A centralized Orchestrator sequences specialized AI agents, handles error‑flows, and manages user hand‑offs. -
FastMCP Tool Server
ambitus-tools-mcp—a MCP server, backed by FastMCP—hosts all external utilities (scrapers, API clients, validators) and the CitationAgent, allowing agents to discover and invoke tools at runtime. -
Structured Agent Outputs
Each agent emits well‑defined JSON payloads, which are persisted to a database and exposed via REST for downstream consumption.
🔑 Key Agents
| Agent Name | Responsibility |
|---|---|
| CompanyResearchAgent | Scrape and ingest public & proprietary sources (Crunchbase, Wikipedia, web) to produce a company profile. |
| IndustryAnalysisAgent | Analyze the company profile via LLM prompts to rank and rationalize potential expansion domains. |
| MarketDataAgent | Retrieve quantitative metrics (market size, CAGR, trends) from external APIs (Google Trends, Statista). |
| CompetitiveLandscapeAgent | Compile and summarize key competitors, their products, market share, and strategic positioning. |
| GapAnalysisAgent | Use LLM reasoning to detect unmet needs and strategic gaps by comparing capabilities vs. competitors. |
| OpportunityAgent | Brainstorm, validate, and rank growth opportunities grounded in data from upstream agents. |
| ReportSynthesisAgent | Aggregate all agent outputs into a citation‑rich final report (Markdown, HTML, PDF). |
| CitationAgent (Tool) | On‑demand retrieval of citations or data snippets, serving all agents via the MCP tool server. |
📖 Documentation
- Docs Index: docs/README.md
- System Overview: docs/system_overview.md
- Agent Specifications: docs/agent_specs.md
Legacy Notion (for archival reference only):
📁 Repository Structure
ambitus-ai-models/
├── docs/ # Architecture & agent specs (Markdown)
│ ├── README.md # Index of spec docs
│ ├── system_overview.md
│ ├── agent_specs.md
│ ├── workflow_examples.md # TODO
│ └── mcp_server.md # TODO
├── notebooks/ # Experimental Jupyter/Colab prototypes
│ ├── Experiment ##- <experiment_name>.ipynb
│ └── ... # Additional experiments in ##-*.ipynb format
├── src/ # Source code
│ ├── agents/ # Individual agent implementations
│ │ ├── __init__.py
│ │ ├── company_research_agent.py
│ │ ├── industry_analysis_agent.py
│ │ ├── market_data_agent.py
│ │ ├── competitive_landscape_agent.py
│ │ ├── gap_analysis_agent.py
│ │ ├── opportunity_agent.py
│ │ ├── report_synthesis_agent.py
│ │ └── citation_agent.py
│ │
│ ├── mcp/ # MCP server configuration and tools
│ │ ├── __init__.py
│ │ ├── server.py # FastMCP server implementation
│ │ ├── tools/ # Tool implementations
│ │ │ ├── __init__.py
│ │ │ └── ... # Individual tool modules
│ │ └── data_sources/ # Data source connectors
│ │ ├── __init__.py
│ │ └── ... # Individual data source modules
│ │
│ ├── api/ # Backend API for web application
│ │ ├── __init__.py
│ │ └── routes.py # API endpoints
│ │
│ └── utils/ # Shared utilities
│ ├── __init__.py
│ └── ...
│
├── .env.example # Example environment variables
├── pyproject.toml # Project configuration and dependencies
├── README.md # Project overview
└── .gitignore # Git ignore file
📧 Contacts
For questions or collaborations, contact:
Lead Developers:
Part of the Next-Gen Market Intelligence Suite
README fetched from the repository yesterday. The original is authoritative.