dexMCP is a Model Context Protocol (MCP) server that wraps the community maintained pypokedex client for the PokeAPI. It exposes curated tools so MCP compatible applications can fetch Pokedex data without custom API plumbing.
- Query any Pokemon by name or national number and receive metric aware base stats.
- Pull localized flavor text so agents can present in universe descriptions for each game version.
- Inspect move learnsets for a chosen game so automation chains pick the right actions.
- Map evolution chains, encounter locations, and breeding requirements without bespoke glue code.
- Run roster analysis with coverage reports and simple moveset tips for battle planning.
get_pokemon- Required:
name_or_dex - Optional: none
- Returns:
PokemonSummarywith stats, types, height, weight, and base experience.
- Required:
get_moves- Required:
name_or_dex,game - Optional: none
- Returns: list of
Moveentries with learn method and optional level.
- Required:
get_sprites- Required:
name_or_dex - Optional:
side(frontorback),variant(default,shiny,female,female_shiny) - Returns:
SpriteURLcontaining the resolved image link.
- Required:
get_descriptions- Required:
name_or_dex - Optional:
language(defaults toen) - Returns: mapping of game version to flavor text strings.
- Required:
analyze_type_coverage- Required:
names_or_dexeslist - Optional: none
- Returns:
TypeCoverageReportsummarizing defensive matchups.
- Required:
explore_abilities- Required:
name_or_dex - Optional: none
- Returns:
AbilityExplorerResultwith effect text and hidden ability flag.
- Required:
plan_evolutions- Required:
name_or_dex - Optional: none
- Returns:
EvolutionReportthat enumerates triggers and branching paths.
- Required:
find_encounters- Required:
name_or_dex - Optional: none
- Returns:
EncounterReportgrouped by location and game version.
- Required:
get_breeding_info- Required:
name_or_dex - Optional:
gameto scope egg moves - Returns:
BreedingInfowith egg groups, hatch steps, gender split, and egg moves.
- Required:
suggest_moveset- Required:
name_or_dex,game - Optional:
limit(default 4),include_tm(defaultfalse) - Returns:
MovesetRecommendationordered by heuristic score.
- Required:
- Python 3.10 or newer.
uvfor dependency management and running scripts.- An MCP aware client (or the Python
mcppackage) that can launch stdio servers. - Internet access so
pypokedexcan query PokeAPI the first time a Pokemon is requested.
git clone https://github.com/RajeevAtla/dexMCP.git
cd dexMCP
uv venv
uv syncThe runtime requirements are mcp (for FastMCP), pypokedex, requests,
dspy-ai, langchain, langchain-openai, gradio, and the transitive
pydantic dependency.
uv run python -m dexmcp.serverThe server speaks MCP over stdio. Configure an MCP client to launch the command above and it will auto discover the tools listed earlier.
The repository ships dspy_client.py, a minimal DSPy client that connects to
this server and calls the appropriate tools to satisfy natural language
requests. Activate your virtual environment and run the curated demo suite:
uv run python dspy_client.py --demoThe agent chains several tools to:
-
Retrieve Garchomp stats and ORAS level up moves.
-
Audit defensive coverage for Pikachu, Garchomp, and Gyarados.
-
Surface Gengar abilities and Eevee evolution branches.
-
List Dratini encounter methods in FireRed and LeafGreen.
-
Summarize Sylveon breeding info and egg moves in Sword and Shield.
-
Recommend a Greninja moveset for Sun and Moon.
Provide your own prompt with:
uv run python dspy_client.py \
"Compare Charizard and Tyranitar defensive coverage in scarlet-violet."Add --demo alongside the prompt to run the canned sequence afterward.
Ensure OPENAI_API_KEY (or another provider key supported by your LangChain
LLM) is present in the environment. Then launch the demo:
uv run python langchain_client.py --demoThe LangChain agent mirrors the DSPy scenarios, exercising the coverage, ability, evolution, encounter, breeding, and moveset tools.
Supply a custom prompt with:
uv run python langchain_client.py \
"Plan a battle ready moveset for gardevoir in scarlet-violet."Use --demo with a prompt to run it first before the guided walkthrough.
The Gradio UI wraps the LangChain agent and calls DexMCP tools over stdio.
Ensure OPENAI_API_KEY (or another provider key supported by your LangChain
LLM) is set.
uv run python gradio_demo.pyOptionally select a different model or share a public link:
uv run python gradio_demo.py --model gpt-4o-mini --shareUse Gradio's reload mode to auto-restart on changes. On Windows, set
GRADIO_SERVER_NAME and GRADIO_SERVER_PORT for the host/port:
set PYTHONPATH=C:\dexMCP
set GRADIO_SERVER_NAME=127.0.0.1
set GRADIO_SERVER_PORT=7860
uv run gradio gradio_demo.pyuv sync --group dev
uv run pytestPytest configuration (including coverage flags) lives in pyproject.toml.
.
|-- dexmcp/
| |-- abilities.py # Ability lookup helper
| |-- api.py # PokeAPI + pypokedex helpers and caching
| |-- breeding.py # Egg group and breeding helpers
| |-- coverage.py # Type coverage analysis
| |-- encounters.py # Wild encounter lookups
| |-- evolution.py # Evolution chain traversal
| |-- models.py # Pydantic schemas
| |-- moveset.py # Moveset recommendation logic
| |-- pokemon.py # Core Pokemon lookup helpers
| `-- server.py # FastMCP server and tool wrappers
|-- assets/
| `-- logo.png # Logo used in the README banner
|-- dspy_client.py # DSPy demo agent that consumes the server
|-- gradio_demo.py # Gradio + LangChain demo UI
|-- langchain_client.py # LangChain demo agent for the same tools
|-- LICENSE.md # MIT License
|-- README.md
pypokedex wraps PokeAPI and caches responses on disk under the user cache
folder. The first lookup for a Pokemon may take a second while data is fetched;
subsequent calls are served from the local cache.
DexMCP is distributed under the MIT License. See LICENSE.md for full terms.
