Poké MCP Server for LlamaIndexGive LlamaIndex instant access to 49 tools to Get Berry, Get Berry Firmness, Get Berry Flavor, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Poké 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 for LlamaIndex
The Poké MCP Server for LlamaIndex is a standout in the Data Management category — giving your AI agent 49 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Poké. "
"You have 49 tools available."
),
)
response = await agent.run(
"What tools are available in Poké?"
)
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 Poké MCP Server
Connect to the PokéAPI through this MCP server to explore the vast world of Pokémon data. This integration allows any AI agent to retrieve detailed information about items, mechanics, and world interactions.
LlamaIndex agents combine Poké tool responses with indexed documents for comprehensive, grounded answers. Connect 49 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
- Berry Research — List all berries, check their firmness levels, and explore flavor profiles like spicy, dry, or sweet.
- Contest Mastery — Query contest types and effects to understand how different moves and items perform in competition.
- Encounter Methods — Discover the various ways Pokémon can be encountered in the wild, from walking in tall grass to fishing.
- Data Exploration — Access paginated lists of resources to browse the entire database systematically.
The Poké MCP Server exposes 49 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 49 Poké tools available for LlamaIndex
When LlamaIndex connects to Poké through Vinkius, your AI agent gets direct access to every tool listed below — spanning api-integration, gaming-data, encyclopedia, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Get berry on Poké
Get berry details
Get berry firmness on Poké
Get berry firmness details
Get berry flavor on Poké
Get berry flavor details
Get contest effect on Poké
Get contest effect details
Get contest type on Poké
Get contest type details
Get encounter condition on Poké
Get encounter condition details
Get encounter condition value on Poké
Get encounter condition value details
Get encounter method on Poké
Get encounter method details
Get evolution chain on Poké
Get evolution chain details
Get evolution trigger on Poké
Get evolution trigger details
Get generation on Poké
Get generation details
Get item on Poké
Get item details
Get item attribute on Poké
Get item attribute details
Get item category on Poké
Get item category details
Get item fling effect on Poké
Get item fling effect details
Get item pocket on Poké
Get item pocket details
Get location on Poké
Get location details
Get location area on Poké
Get location area details
Get pal park area on Poké
Get pal park area details
Get pokedex on Poké
Get pokedex details
Get region on Poké
Get region details
Get super contest effect on Poké
Get super contest effect details
Get version on Poké
Get version details
Get version group on Poké
Get version group details
List berries on Poké
List berries
List berry firmnesses on Poké
List berry firmnesses
List berry flavors on Poké
List berry flavors
List contest effects on Poké
List contest effects
List contest types on Poké
List contest types
List encounter condition values on Poké
List encounter condition values
List encounter conditions on Poké
List encounter conditions
List encounter methods on Poké
List encounter methods
List evolution chains on Poké
List evolution chains
List evolution triggers on Poké
List evolution triggers
List generations on Poké
List generations
List item attributes on Poké
List item attributes
List item categories on Poké
List item categories
List item fling effects on Poké
List item fling effects
List item pockets on Poké
List item pockets
List items on Poké
List items
List location areas on Poké
List location areas
List locations on Poké
List locations
List pal park areas on Poké
List pal park areas
List pokedexes on Poké
List pokedexes
List regions on Poké
List regions
List super contest effects on Poké
List super contest effects
List version groups on Poké
List version groups
List versions on Poké
List versions
Query graphql on Poké
Execute a GraphQL query against PokéAPI
Connect Poké to LlamaIndex via MCP
Follow these steps to wire Poké into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Poké MCP Server
LlamaIndex provides unique advantages when paired with Poké through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Poké tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Poké tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Poké, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Poké tools were called, what data was returned, and how it influenced the final answer
Poké + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Poké MCP Server delivers measurable value.
Hybrid search: combine Poké real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Poké 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 Poké for fresh data
Analytical workflows: chain Poké queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Poké in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Poké immediately.
"List the first 10 berries available in the database."
"What are the effects of the contest type 'cool'?"
"Show me the different encounter methods available."
Troubleshooting Poké MCP Server with LlamaIndex
Common issues when connecting Poké to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPoké + LlamaIndex FAQ
Common questions about integrating Poké 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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