agentic-ai

Deal intelligence for agents: SEC-verified financials, validation, institutional deal scoring.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
80%
Naming quality
83%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~1,590Tokens (tool definitions)
~824 BTypical response size
Moderate attention impact (1.24% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "agentic-ai": {
      "url": "https://agentic-ai-production-e711.up.railway.app/mcp"
    }
  }
}

Remote endpoints

https://agentic-ai-production-e711.up.railway.app/mcpstreamable-http

What it can do

Tool inventory

Tools (8)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢investor_intro_preview(asset_class, target_raise_m, industry, geography, ebitda_m)

FREE, no API key. Use when someone wants to be connected with investors for a raise. Runs DEALITHIC's matching engine against 93,000+ funds, family offices and angels and returns how many fit and what kinds of investors they are (counts only: no firm names or contacts). asset_class is one of pe, vc, growth, credit, real_estate, infrastructure, preferred_equity, equity, public_equity, other. target_raise_m is the raise in USD millions. If the result looks useful, offer request_intro to book a demo where names and contacts are released.

Input Schema

{
  "type": "object",
  "properties": {
    "asset_class": {
      "title": "Asset Class",
      "type": "string"
    },
    "target_raise_m": {
      "title": "Target Raise M",
      "type": "number"
    },
    "industry": {
      "title": "Industry",
      "type": "string"
    },
    "geography": {
      "default": "",
      "title": "Geography",
      "type": "string"
    },
    "ebitda_m": {
      "default": null,
      "title": "Ebitda M",
      "type": "number"
    }
  },
  "required": [
    "asset_class",
    "target_raise_m",
    "industry"
  ],
  "title": "investor_intro_previewArguments"
}
🟢lp_match_preview(fund_strategy, target_fund_size_m, lp_types)

FREE, no API key. Use when a fund manager (GP) wants to find LPs for a fund they are raising. Returns how many LP-type investors in DEALITHIC's network fit each LP type (pension, endowment, foundation, sovereign_wealth, fund_of_funds, family_office): counts only, no names or contacts. Counts are by LP type and are not yet scored against the strategy or fund size. target_fund_size_m is in USD millions. lp_types optionally narrows the types. If useful, offer request_lp_intro to book a demo where specific LPs are released.

Input Schema

{
  "type": "object",
  "properties": {
    "fund_strategy": {
      "title": "Fund Strategy",
      "type": "string"
    },
    "target_fund_size_m": {
      "title": "Target Fund Size M",
      "type": "number"
    },
    "lp_types": {
      "default": null,
      "items": {
        "type": "string"
      },
      "title": "Lp Types",
      "type": "array"
    }
  },
  "required": [
    "fund_strategy",
    "target_fund_size_m"
  ],
  "title": "lp_match_previewArguments"
}
🟡request_lp_intro(name, email, firm, fund_summary, consent)

FREE, no API key. Records a fund manager's request to be introduced to DEALITHIC and booked into a demo about raising their fund from LPs. Only call this after the person has explicitly agreed to be contacted by email, and set consent=true only in that case.

Input Schema

{
  "type": "object",
  "properties": {
    "name": {
      "title": "Name",
      "type": "string"
    },
    "email": {
      "title": "Email",
      "type": "string"
    },
    "firm": {
      "title": "Firm",
      "type": "string"
    },
    "fund_summary": {
      "title": "Fund Summary",
      "type": "string"
    },
    "consent": {
      "title": "Consent",
      "type": "boolean"
    }
  },
  "required": [
    "name",
    "email",
    "firm",
    "fund_summary",
    "consent"
  ],
  "title": "request_lp_introArguments"
}
🟡request_intro(name, email, company, deal_summary, consent)

FREE, no API key. Records a request to be introduced to DEALITHIC and booked into a demo, where matched investors are revealed. Only call this after the person has explicitly agreed to be contacted by email about their raise, and set consent=true only in that case.

Input Schema

{
  "type": "object",
  "properties": {
    "name": {
      "title": "Name",
      "type": "string"
    },
    "email": {
      "title": "Email",
      "type": "string"
    },
    "company": {
      "title": "Company",
      "type": "string"
    },
    "deal_summary": {
      "title": "Deal Summary",
      "type": "string"
    },
    "consent": {
      "title": "Consent",
      "type": "boolean"
    }
  },
  "required": [
    "name",
    "email",
    "company",
    "deal_summary",
    "consent"
  ],
  "title": "request_introArguments"
}
🟢sec_extract(ticker)

Verified financial statements and derived metrics for a US-listed ticker, extracted from SEC EDGAR XBRL filings. Every value carries provenance (the exact filing, form, and tag it came from); missing facts are null, never 0. $0.25/call after free trial.

Input Schema

{
  "type": "object",
  "properties": {
    "ticker": {
      "title": "Ticker",
      "type": "string"
    }
  },
  "required": [
    "ticker"
  ],
  "title": "sec_extractArguments"
}
🟢validate_financials(financials)

Institutional validation pass over company financials: tax-rate sanity, EBITDA/EBIT bridge, growth continuity vs historical CAGR, capex ratio, working-capital stability. Returns integrity score + severity-ranked flags. $0.50/call after free trial.

Input Schema

{
  "type": "object",
  "properties": {
    "financials": {
      "additionalProperties": true,
      "title": "Financials",
      "type": "object"
    }
  },
  "required": [
    "financials"
  ],
  "title": "validate_financialsArguments"
}
🟢company_report(ticker, market, context)

The flagship: eight-lens institutional analysis of a US-listed company, grounded entirely in SEC-verified figures with per-field filing citations. Lenses: equity research, investment banking, strategy consulting, turnaround ops, comparables, capital markets, disclosure audit, and Charlie Munger's 10 mental models — plus an executive synthesis. Optionally pass `market` (e.g. {"price": 12.34, "market_cap_m": 5000}) from your own data source to enable valuation views, and `context` — your own deal materials (CIM extracts, computed valuations), treated as caller-asserted rather than SEC-verified. $25.00/call after free trial; allow ~60s.

Input Schema

{
  "type": "object",
  "properties": {
    "ticker": {
      "title": "Ticker",
      "type": "string"
    },
    "market": {
      "additionalProperties": true,
      "default": null,
      "title": "Market",
      "type": "object"
    },
    "context": {
      "default": null,
      "title": "Context",
      "type": "string"
    }
  },
  "required": [
    "ticker"
  ],
  "title": "company_reportArguments"
}
🟢deal_score(deal)

Full underwriting chain on a deal profile: financial integrity → trend → industry position → stress tests → conviction score, plus a risk register and investment thesis (and an rNPV valuation band for biotech deals with `indications`). $2.00/call after free trial.

Input Schema

{
  "type": "object",
  "properties": {
    "deal": {
      "additionalProperties": true,
      "title": "Deal",
      "type": "object"
    }
  },
  "required": [
    "deal"
  ],
  "title": "deal_scoreArguments"
}

Community

Rate this Server

Evidence

Recent observations

verifiedversion not recorded8 tools
verifiedversion not recorded6 tools
verifiedversion not recorded6 tools
verifiedversion not recorded6 tools
verifiedversion not recorded6 tools
verifiedversion not recorded4 tools
verifiedversion not recorded4 tools