Polymarket MCP Tool
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| prediction_markets_trending_topicsA | Use when analysing a user’s portfolio and you need external sentiment from prediction markets. Retrieves today’s trending Polymarket topics (ordered by 24-hour volume).
Pass any slug from this list to Returnsstr A JSON array (string) of topic slugs ordered by 24-hour volume, e.g. '["Trump-Presidency", "Oil-Prices", "Iran"]'. |
| prediction_markets_markets_by_topicA | Call after you have a Polymarket topic slug (from the user or
Parameterstopic_slug : str Identifier such as "trump-presidency". limit : int, default 10 Number of markets to return, ranked by 24-hour volume (desc). Returnsstr
JSON array of objects with the schema:
[
{
"title": "Trump to win 2024?",
"volume": 123456.78,
"outcomes": [
{"option": "Yes", "probability": 0.42},
{"option": "No", "probability": 0.58}
]
},
…
]
Parse with |
| search_prediction_marketsB | Search prediction markets by any term. Parameterssearch_term : str Identifier such as "argentina". Returnsstr
JSON array of objects with the schema:
[
{
"title": "Trump to win 2024?",
"volume": 123456.78,
"outcomes": [
{"option": "Yes", "probability": 0.42},
{"option": "No", "probability": 0.58}
]
},
…
]
Parse with |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
The three tools have distinct primary purposes: getting trending topics, fetching markets by topic, and searching markets by term. However, there is some functional overlap between `prediction_markets_markets_by_topic` and `search_prediction_markets` as both return market data, which could cause minor confusion about when to use each.
All tool names follow a consistent snake_case pattern with a clear `prediction_markets_` prefix and descriptive suffixes (`trending_topics`, `markets_by_topic`, `search_prediction_markets`). The naming is predictable and follows a logical structure throughout.
With only 3 tools, the server feels somewhat thin for a prediction markets domain. While the tools cover basic discovery and search functionality, the limited count suggests potential gaps in comprehensive market interaction capabilities that might be expected from such a service.
The tools provide good discovery and search capabilities but lack any market interaction functions (like placing bets, viewing user positions, or managing portfolios). For a prediction markets server, this represents notable gaps in the full lifecycle of market participation, though the provided tools work well together for information gathering.