PokéAPI MCP Server for LlamaIndex 20 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PokéAPI as an MCP tool provider through 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 PokéAPI. "
"You have 20 tools available."
),
)
response = await agent.run(
"What tools are available in PokéAPI?"
)
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 PokéAPI MCP Server
Connect PokéAPI, the definitive Pokémon database, to any AI agent and explore comprehensive data on all 1000+ Pokémon species, moves, abilities, types, items, and evolution chains through natural language.
LlamaIndex agents combine PokéAPI tool responses with indexed documents for comprehensive, grounded answers. Connect 20 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
- Pokémon Lookup — Get detailed stats, types, abilities, height, weight, and sprite images for any Pokémon
- Species Data — Access capture rates, egg groups, growth rates, habitats, and flavor text from every game version
- Type Effectiveness — Check damage relations for all 18 types to plan battle strategies
- Move Database — Search moves by power, accuracy, PP, and effects with full metadata
- Evolution Chains — View complete family trees with all evolution conditions and triggers
- Item Catalog — Browse held items, Poké Balls, and berries with effects and costs
- Regional Data — Explore generations, regions, and Pokédex variants
The PokéAPI MCP Server exposes 20 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 PokéAPI to LlamaIndex via MCP
Follow these steps to integrate the PokéAPI 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 20 tools from PokéAPI
Why Use LlamaIndex with the PokéAPI MCP Server
LlamaIndex provides unique advantages when paired with PokéAPI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PokéAPI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PokéAPI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PokéAPI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PokéAPI tools were called, what data was returned, and how it influenced the final answer
PokéAPI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PokéAPI MCP Server delivers measurable value.
Hybrid search: combine PokéAPI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PokéAPI 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 PokéAPI for fresh data
Analytical workflows: chain PokéAPI queries with LlamaIndex's data connectors to build multi-source analytical reports
PokéAPI MCP Tools for LlamaIndex (20)
These 20 tools become available when you connect PokéAPI to LlamaIndex via MCP:
get_ability
Get detailed ability information
get_berry
Get detailed berry information
get_evolution_chain
). Get evolution chain details
get_generation
Get generation details
get_item
Get detailed item information
get_move
Get detailed move information
get_pokedex
Get detailed Pokédex information
get_pokemon
), types, abilities, height, weight, and sprite images. Accepts either the Pokémon ID or name. Get detailed Pokémon information
get_pokemon_species
Get Pokémon species information
get_region
Get region details
get_type
Get type effectiveness and Pokémon
list_abilities
Each ability grants a passive effect to the Pokémon that has it. List all Pokémon abilities
list_berries
Berries are held items with various effects when consumed. List all berries
list_generations
List all Pokémon generations
list_items
List all held items
list_moves
List all Pokémon moves
list_pokedexes
) with their associated regions and Pokémon entries. List all Pokédexes
list_pokemon
Use limit and offset to browse through the full catalog of 1000+ Pokémon. List all Pokémon names with pagination
list_regions
) with their associated locations, Pokédexes, and version groups. List all Pokémon regions
list_types
). There are 18 types in total. List all Pokémon types
Example Prompts for PokéAPI in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with PokéAPI immediately.
"Show me everything about Pikachu."
"What types are strong against Fire?"
"What's the evolution chain for Eevee?"
Troubleshooting PokéAPI MCP Server with LlamaIndex
Common issues when connecting PokéAPI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPokéAPI + LlamaIndex FAQ
Common questions about integrating PokéAPI 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 PokéAPI 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 PokéAPI to LlamaIndex
Get your token, paste the configuration, and start using 20 tools in under 2 minutes. No API key management needed.