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search_token_details

Retrieve comprehensive cryptocurrency token information including contract details, pricing data, and blockchain specifications to support trading and analysis decisions.

Instructions

Search and retrieve details about single token.
If only address or symbol is needed, use get_official_token_address first.

Expects a TokenSearchRequest, returns a list of TokenDetailsResponse.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_search_requestsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_search_responsesYes

Implementation Reference

  • MCP tool handler function for search_token_details. Registers the tool via @mcp.tool() decorator and implements the logic by delegating to armor_client.search_token().
    @mcp.tool()
    async def search_token_details(token_search_requests: TokenSearchRequest) -> TokenSearchResponseContainer:
        """
        Search and retrieve details about single token.
        If only address or symbol is needed, use get_official_token_address first.
        
        Expects a TokenSearchRequest, returns a list of TokenDetailsResponse.
        """
        if not armor_client:
            return [{"error": "Not logged in"}]
        try:
            result: TokenSearchResponseContainer = await armor_client.search_token(token_search_requests)
            return result
        except Exception as e:
            return [{"error": str(e)}]
  • Pydantic input schema model for the tool: TokenSearchRequest defining query, sort_by, sort_order, and limit parameters.
    class TokenSearchRequest(BaseModel):
        query: str = Field(description="token symbol or address")
        sort_by: Optional[Literal['decimals', 'holders', 'jupiter', 'verified', 'liquidityUsd', 'marketCapUsd', 'priceUsd', 'totalBuys', 'totalSells', 'totalTransactions', 'volume_5m', 'volume', 'volume_15m', 'volume_30m', 'volume_1h', 'volume_6h', 'volume_12h', 'volume_24h']] = Field(description="Sort token data results by this field")
        sort_order: Optional[Literal['asc', 'desc']] = Field(default='desc', description="The order of the sorted results")
        limit: Optional[int] = Field(default=10, description="The number of results to return from the search. Use default unless specified. Should not be over 30 if looking up multiple tokens.")
  • Pydantic output schema model for individual token details: TokenSearchResponse with fields like name, symbol, mint_address, market data, etc.
    class TokenSearchResponse(BaseModel):
        name: str = Field(description="name of the token")
        symbol: str = Field(description="symbol of the token")
        mint_address: Optional[str] = Field(description="mint address of the token")
        decimals: Optional[int] = Field(description="number of decimals of the token, returns only if include_details is True")
        image: Optional[str] = Field(description="image url of the token, returns only if include_details is True")
        holders: Optional[int] = Field(description="number of holders of the token, returns only if include_details is True")
        jupiter: Optional[bool] = Field(description="whether the token is supported by Jupiter, returns only if include_details is True")
        verified: Optional[bool] = Field(description="whether the token is verified, returns only if include_details is True")
        liquidityUsd: Optional[float] = Field(description="liquidity of the token in USD, returns only if include_details is True")
        marketCapUsd: Optional[float] = Field(description="market cap of the token in USD, returns only if include_details is True")
        priceUsd: Optional[float] = Field(description="price of the token in USD, returns only if include_details is True")
        lpBurn: Optional[float] = Field(description="lp burn of the token, returns only if include_details is True")
        market: Optional[str] = Field(description="market of the token, returns only if include_details is True")
        freezeAuthority: Optional[str] = Field(description="freeze authority of the token, returns only if include_details is True")
        mintAuthority: Optional[str] = Field(description="mint authority of the token, returns only if include_details is True")
        poolAddress: Optional[str] = Field(description="pool address of the token, returns only if include_details is True")
        totalBuys: Optional[int] = Field(description="total number of buys of the token, returns only if include_details is True")
        totalSells: Optional[int] = Field(description="total number of sells of the token, returns only if include_details is True")
        totalTransactions: Optional[int] = Field(description="total number of transactions of the token, returns only if include_details is True")
        volume: Optional[float] = Field(description="volume of the token, returns only if include_details is True")
        volume_5m: Optional[float] = Field(description="volume of the token in the last 5 minutes, returns only if include_details is True")
        volume_15m: Optional[float] = Field(description="volume of the token in the last 15 minutes, returns only if include_details is True")
        volume_30m: Optional[float] = Field(description="volume of the token in the last 30 minutes, returns only if include_details is True")
        volume_1h: Optional[float] = Field(description="volume of the token in the last 1 hour, returns only if include_details is True")
        volume_6h: Optional[float] = Field(description="volume of the token in the last 6 hours, returns only if include_details is True")
        volume_12h: Optional[float] = Field(description="volume of the token in the last 12 hours, returns only if include_details is True")
        volume_24h: Optional[float] = Field(description="volume of the token in the last 24 hours, returns only if include_details is True")
  • Pydantic container model for the tool output: TokenSearchResponseContainer wrapping a list of TokenSearchResponse.
    class TokenSearchResponseContainer(BaseModel):
        token_search_responses: List[TokenSearchResponse]
  • Supporting method in ArmorWalletAPIClient that performs the HTTP API call to the backend for token search, used by the tool handler.
    async def search_token(self, data: TokenSearchRequest) -> TokenSearchResponseContainer:
        """Get details of a token."""
        payload = data.model_dump(exclude_none=True)
        return await self._api_call("POST", "tokens/search-token/", payload)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the input/output types (TokenSearchRequest/TokenDetailsResponse) but doesn't describe what 'details' include, whether this is a read-only operation, any rate limits, authentication requirements, or error conditions. The description provides minimal behavioral context beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with three sentences that each serve a purpose: stating the core function, providing usage guidance, and specifying input/output types. It's front-loaded with the main purpose and avoids unnecessary verbiage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which handles return values) but zero parameter documentation and no annotations, the description is moderately complete. It covers the basic purpose and provides some usage guidance, but fails to compensate for the complete lack of parameter documentation or behavioral context that annotations would normally provide.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 1 parameter (token_search_requests), the description provides no information about what constitutes a TokenSearchRequest, what fields it contains, or how to structure it. The description mentions the parameter type name but adds no semantic meaning beyond what's already implied by the schema structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('search and retrieve details') and resource ('single token'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this from sibling tools like 'search_official_token_address' or 'get_token_candle_data' beyond a brief alternative mention.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear guidance on when to use an alternative tool ('get_official_token_address first' for address or symbol only), which helps the agent make appropriate choices. However, it doesn't specify when NOT to use this tool or compare it to other potential alternatives like 'get_top_trending_tokens'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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