EPA Computational Toxicology MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add EPA Computational Toxicology as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 EPA Computational Toxicology. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in EPA Computational Toxicology?"
)
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 EPA Computational Toxicology MCP Server
Connect to the US Environmental Protection Agency's (EPA) Center for Computational Toxicology and Exposure (CCTE) and explore a massive repository of chemical data through natural conversation.
LlamaIndex agents combine EPA Computational Toxicology tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Chemical Search — Find substances by name, CAS Registry Number (CASRN), or DTXSID
- Physicochemical Properties — Retrieve melting points, boiling points, logP, and water solubility
- Hazard Assessments — Access toxicity values, NOAELs, and points-of-departure from ToxValDB
- Exposure Predictions — Explore predicted exposure levels and product use categories via ExpoCast and CPDat
- Bioactivity Screening — Analyze ToxCast/Tox21 high-throughput screening results for thousands of assays
- Environmental Fate — Check persistence, transport, and biodegradation metrics
The EPA Computational Toxicology MCP Server exposes 10 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 EPA Computational Toxicology to LlamaIndex via MCP
Follow these steps to integrate the EPA Computational Toxicology 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 10 tools from EPA Computational Toxicology
Why Use LlamaIndex with the EPA Computational Toxicology MCP Server
LlamaIndex provides unique advantages when paired with EPA Computational Toxicology through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine EPA Computational Toxicology tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain EPA Computational Toxicology tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query EPA Computational Toxicology, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what EPA Computational Toxicology tools were called, what data was returned, and how it influenced the final answer
EPA Computational Toxicology + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the EPA Computational Toxicology MCP Server delivers measurable value.
Hybrid search: combine EPA Computational Toxicology real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query EPA Computational Toxicology 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 EPA Computational Toxicology for fresh data
Analytical workflows: chain EPA Computational Toxicology queries with LlamaIndex's data connectors to build multi-source analytical reports
EPA Computational Toxicology MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect EPA Computational Toxicology to LlamaIndex via MCP:
get_bioactivity_summary
Retrieve a summary of high-throughput screening results from ToxCast/Tox21 assays
get_chemical_details
Get comprehensive metadata and identification details for a specific chemical using its DTXSID
get_chemical_lists
Identify which chemical lists (regulatory, research, or commercial) this chemical belongs to
get_chemical_synonyms
Retrieve all known synonyms and alternative names for a specific chemical
get_exposure_summary
Retrieve predicted exposure levels and product use data (ExpoCast/CPDat)
get_fate_and_transport
Retrieve environmental fate and transport data (e.g., half-life, bioconcentration)
get_hazard_summary
Retrieve a summary of toxicity values and hazard assessment data from ToxValDB
get_physicochemical_properties
Retrieve predicted and experimental physicochemical properties (e.g., melting point, logP, solubility) for a chemical
search_chemical_by_casrn
Search for chemicals by their CAS Registry Number (CASRN)
search_chemical_by_name
Search for chemicals by common, IUPAC, or synonym names in the EPA CompTox database
Example Prompts for EPA Computational Toxicology in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with EPA Computational Toxicology immediately.
"Search for the chemical properties of Bisphenol A."
"What is the hazard summary for CAS 80-05-7?"
"Find predicted exposure data for DTXSID7020182."
Troubleshooting EPA Computational Toxicology MCP Server with LlamaIndex
Common issues when connecting EPA Computational Toxicology to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEPA Computational Toxicology + LlamaIndex FAQ
Common questions about integrating EPA Computational Toxicology 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 EPA Computational Toxicology 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 EPA Computational Toxicology to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.