address_labelsGet the standard labels for one wallet address.
This tool returns identity, behavioural, and protocol labels. It does not return premium labels.
| Name | Required | Description | Default |
|---|---|---|---|
| request | Yes | Request for the standard labels of one wallet address. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It clearly presents this as a read-only lookup, enumerates the label categories returned, and usefully discloses that premium labels are not included. Pagination and rate limits are not mentioned, but the output schema covers the return shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The main action and scope are front-loaded, and the only extra sentence explains a meaningful limitation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-address lookup with a fully documented nested input schema and output schema, the description provides enough context to select and call the tool correctly. It would be slightly stronger with an explicit pointer to a premium-label alternative, but that is not necessary for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for all parameters, so the baseline is 3. The description does not add parameter-level detail beyond 'one wallet address', but that is acceptable because the schema already documents address, chain, page, and perPage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get the standard labels for one wallet address.' It then clarifies what kind of labels are returned (identity, behavioural, protocol) and explicitly excludes premium labels, which differentiates it from a potential premium-label lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description communicates scope and an explicit exclusion: it returns standard labels, not premium labels. However, it never names an alternative tool or states a broader when-to-use policy relative to sibling address_* tools, so the agent must infer usage context from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (address vs token vs prediction market vs transaction). Overlapping tools like token_discovery_screener and nansen_score_top_tokens, or address_counterparties and address_related_addresses, are explicitly disambiguated with detailed usage guidance. A few tools (token_flows vs token_recent_flows_summary) require careful reading but are still distinguishable.
Tool names consistently use snake_case with resource prefixes (address_*, token_*, prediction_market_*). Minor deviations include general_search, growth_chain_rank, and nansen_score_top_tokens, and some names like smart_traders_and_funds_perp_trades are verbose but still follow the pattern.
38 tools is a heavy surface, but it matches Nansen's broad domain covering address analytics, token intelligence, prediction markets, and Hyperliquid perps. The count is on the high end and may overwhelm agents, but each tool appears to serve a distinct function within a reasonably scoped analytics platform.
The tool surface is comprehensive: address lifecycle (portfolio, transactions, balances, counterparties, PnL), token analytics (price, OHLCV, indicators, flows, transfers, holders, discovery), prediction markets (lookup, orderbook, trades, top holders, PnL), and specialized features (smart money, chain rankings). No obvious dead ends or missing critical operations are apparent.