PubChem MCP Server for LlamaIndex 3 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PubChem 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 PubChem. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in PubChem?"
)
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 PubChem MCP Server
Connect your AI agent to PubChem — the world's largest open chemistry database, maintained by the National Center for Biotechnology Information (NCBI/NIH).
LlamaIndex agents combine PubChem tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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.
What you can do
- Compound Search — Find chemical compounds by common name (aspirin, caffeine, glucose), IUPAC name, or CAS number across 116M+ indexed compounds
- CID Lookup — Get comprehensive molecular data for any compound by its PubChem Compound ID including formula, weight, SMILES, InChI, and physicochemical properties
- Formula Search — Find all compounds matching a specific molecular formula (e.g., C9H8O4 for aspirin)
The PubChem MCP Server exposes 3 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 PubChem to LlamaIndex via MCP
Follow these steps to integrate the PubChem 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 3 tools from PubChem
Why Use LlamaIndex with the PubChem MCP Server
LlamaIndex provides unique advantages when paired with PubChem through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PubChem tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PubChem tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PubChem, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PubChem tools were called, what data was returned, and how it influenced the final answer
PubChem + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PubChem MCP Server delivers measurable value.
Hybrid search: combine PubChem real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PubChem 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 PubChem for fresh data
Analytical workflows: chain PubChem queries with LlamaIndex's data connectors to build multi-source analytical reports
PubChem MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect PubChem to LlamaIndex via MCP:
get_pubchem_compound
Get full chemical data for a PubChem compound by CID
search_pubchem
Returns molecular formula, weight, SMILES, InChI, XLogP, hydrogen bond donors/acceptors, and complexity. Try: aspirin, caffeine, glucose, penicillin, dopamine. Search PubChem for chemical compounds by name
search_pubchem_formula
g. C9H8O4, C8H10N4O2, H2O) and find matching compounds. Find compounds by molecular formula
Example Prompts for PubChem in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with PubChem immediately.
"What are the molecular properties of aspirin?"
"Search for compounds with the molecular formula C8H10N4O2."
"Get the full chemical details for PubChem compound CID 5090."
Troubleshooting PubChem MCP Server with LlamaIndex
Common issues when connecting PubChem to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPubChem + LlamaIndex FAQ
Common questions about integrating PubChem 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?
Connect PubChem with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect PubChem to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.