PitchBook MCP Server for LlamaIndex 13 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PitchBook as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to PitchBook. "
"You have 13 tools available."
),
)
response = await agent.run(
"What tools are available in PitchBook?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About PitchBook MCP Server
What you can do
Connect AI agents to the PitchBook Direct Data API for comprehensive private market intelligence:
LlamaIndex agents combine PitchBook tool responses with indexed documents for comprehensive, grounded answers. Connect 13 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
- Search companies across global private and public markets with industry and status filters
- Get complete company profiles with founding dates, headquarters, employees, and industry classifications
- Track financing history from Seed to Series D+ with deal sizes, investor syndicates, and valuations
- Research deals including VC investments, M&A transactions, LBOs, and public offerings
- Analyze investors — VC firms, PE firms, angels, family offices, and corporate venture arms
- Explore investment funds with AUM, vintage years, stage preferences, and sector focus
- Find professionals — founders, executives, board members, and key decision-makers
- Identify limited partners — pension funds, endowments, sovereign wealth funds, and family offices
- Get AI-powered VC exit predictions for portfolio companies with IPO and acquisition probability scores
The PitchBook MCP Server exposes 13 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect PitchBook to LlamaIndex via MCP
Follow these steps to integrate the PitchBook MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 13 tools from PitchBook
Why Use LlamaIndex with the PitchBook MCP Server
LlamaIndex provides unique advantages when paired with PitchBook through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PitchBook tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PitchBook tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PitchBook, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PitchBook tools were called, what data was returned, and how it influenced the final answer
PitchBook + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PitchBook MCP Server delivers measurable value.
Hybrid search: combine PitchBook real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PitchBook to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying PitchBook for fresh data
Analytical workflows: chain PitchBook queries with LlamaIndex's data connectors to build multi-source analytical reports
PitchBook MCP Tools for LlamaIndex (13)
These 13 tools become available when you connect PitchBook to LlamaIndex via MCP:
get_companies
Returns company names, statuses, industries, locations, and key identifiers. Use optional filters to narrow results by industry, location, company status (Active, Acquired, Closed, IPO), or other attributes. Results follow JSON:API format with pagination metadata. Use this to find startups, established companies, or emerging players in specific sectors. Search and list companies in the PitchBook private market database
get_company
Requires the company ID from get_companies results. Use this for comprehensive company due diligence and background research. Get detailed profile for a specific company in PitchBook
get_company_financing
Each round shows announced date, amount raised (USD), lead investors, participating investors, deal structure, and post-money valuation if disclosed. Requires the company ID from get_companies or get_company results. Use this to analyze a company's fundraising trajectory, total capital raised, and investor syndicate composition. Get complete funding/financing history for a specific company
get_deal
), announced date, deal size (if disclosed), all participating companies, investors, funds, and financial advisors, deal terms and structure, and any publicly available valuation data. Requires the deal ID from get_deals results. Use this for deep analysis of specific transactions, competitive deal intelligence, or investment thesis validation. Get detailed information about a specific deal/transaction
get_deals
Returns deal names, types (VC Deal, M&A, IPO, LBO, etc.), announced dates, deal sizes (if disclosed), and participating entities. Use optional filters to narrow by deal type, industry, location, or date range. Results follow JSON:API format with pagination metadata. Use this to track recent deal activity, identify active investors, or monitor M&A trends. Search and list deals (VC investments, M&A, offerings) in PitchBook
get_fund
Requires the fund ID from get_funds results. Use this for fund-level due diligence, LP allocation decisions, or understanding fund investment strategies. Get detailed information about a specific investment fund
get_funds
Returns fund names, types, sizes (if disclosed), vintages (year), investor/firm names, and key identifiers. Use optional filters to narrow by fund type, vintage year, fund size, or investor. Use this to analyze fund raising trends, identify active funds in a vintage, or research fund managers for LP due diligence. Search and list investment funds in PitchBook
get_investor
), sector focus areas, geographic focus, notable portfolio companies, and key personnel. Requires the investor ID from get_investors results. Use this for thorough investor due diligence, LP fundraising research, or understanding investment firm strategies. Get detailed profile for a specific investor/firm
get_investors
Returns investor names, types (VC, PE, Angel, Corporate VC, etc.), headquarters locations, fund counts, total AUM (if disclosed), and key identifiers. Use optional filters to narrow by investor type, location, or fund size. Use this to find potential investors, research competitor firms, or map the investment landscape. Search and list investors (VC firms, angels, PE firms) in PitchBook
get_limited_partners
Returns LP names, types, locations, total commitments (if disclosed), and key identifiers. Use optional filters to narrow by LP type, location, or commitment size. Use this for LP fundraising research, understanding LP allocation trends, or identifying potential fund investors. Search and list limited partners (LPs) in PitchBook
get_professional
Requires the professional ID from get_professionals results. Use this for thorough individual due diligence, founder background checks, or mapping professional deal flow networks. Get detailed profile for a specific professional
get_professionals
Returns names, current titles, organizational affiliations, locations, and key identifiers. Use optional filters to narrow by title, organization, or location. Use this to find key decision-makers, research founder backgrounds, or map professional networks in the startup ecosystem. Search and list professionals (founders, executives, investors) in PitchBook
get_vc_exit_predictor
Returns the predicted exit likelihood score, predicted exit type (IPO, Acquisition, Secondary), predicted exit timeframe, and comparable exits used in the model. Requires the company ID from get_companies results. Use this to assess exit probability for portfolio companies, identify likely IPO candidates, or evaluate acquisition potential of target companies. Note: This is a predictive model output, not a guaranteed outcome. Get AI-powered VC exit prediction for a specific company
Example Prompts for PitchBook in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with PitchBook immediately.
"Search for artificial intelligence startups that raised a Series A round in the last 6 months."
Troubleshooting PitchBook MCP Server with LlamaIndex
Common issues when connecting PitchBook to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPitchBook + LlamaIndex FAQ
Common questions about integrating PitchBook MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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Connect PitchBook to LlamaIndex
Get your token, paste the configuration, and start using 13 tools in under 2 minutes. No API key management needed.