Knowledge & discovery

These five tools are how your agent orients itself. Use them before writing SQL — guessing a table name costs more than searching for it.

Available tools

Tool	Description
`search_schemas`	Search Allium’s table catalog, or fetch one table’s full schema by ID
`search_docs`	Semantic search across Allium’s public documentation
`browse_docs`	Navigate the documentation tree like a filesystem
`search_terminal`	Search public Terminal dashboards built by Allium’s analysts
`get_terminal_results`	Fetch a Terminal chart’s SQL or its latest precomputed rows

Check search_terminal first for common topics. An analyst-built dashboard often already answers the question, and reading its SQL is cheaper and more reliable than writing your own.

Search schemas

One tool covers both discovery and fetch-by-ID.

Discovery
Fetch by ID

Search by keywords, table names, tags, or a description of the data:

{
  "name": "search_schemas",
  "arguments": {
    "query": "erc20 token transfers",
    "limit": 5
  }
}

Each hit returns the table ID, database, schema, table name, description, row count, tags, and score. Bodies are omitted by default so the payload stays small.

Once you know the table, fetch its full schema. id is the dotted <database>.<schema>.<table> form returned in a prior hit:

{
  "name": "search_schemas",
  "arguments": {
    "id": "ethereum.raw.token_transfers"
  }
}

Fetch-by-ID bypasses search and always includes the full markdown body — column names, types, and descriptions.

Parameter	Default	Notes
`query`	—	Mutually exclusive with `id`
`id`	—	Dotted table ID. Always returns full content
`include_content`	`false`	Full markdown body per hit. Use a `limit` of 1–3 when true
`limit`	`5`	Max 20. Use 3–5 for discovery
`search_mode`	`basic`	`basic` is BM25 keyword ranking, sub-millisecond. `advanced` is hybrid vector + keyword with better recall on natural-language queries

advanced search mode isn’t enabled for every organization. If it returns an error, retry with search_mode: "basic" or contact [email protected].

Search and browse documentation

search_docs is semantic search over docs.allium.so — use it for data-model questions, API usage, and querying best practices.

{
  "name": "search_docs",
  "arguments": { "query": "how to query DEX trades" }
}

browse_docs walks the same content as a filesystem. Every directory has an _index.md listing its contents with descriptions.

{
  "name": "browse_docs",
  "arguments": { "path": "historical-data/_index.md" }
}

How to navigate efficiently:

Read _index.md at the root to see the top-level sections.
Read a section’s _index.md (for example historical-data/_index.md).
Drill down through subdirectory index files.
Read the specific file for table schemas, SQL examples, or API specs.

Path form	Result
`""` or `"."`	Root directories and files
`"api"`	Contents of the `api/` directory
`"api/developer/prices/token-latest-price.md"`	That file’s content

Never read files blindly. Read the _index.md in a directory first — it tells you which file you actually want. For semantic lookup, use search_docs instead of guessing paths.

Realtime tool descriptions include a docs_path pointing at the exact file that documents their supported chains, edge cases, and response shape. Pass it straight to browse_docs.

Terminal dashboards

Terminal is Allium’s library of public, analyst-built dashboards. Two tools read it, and neither consumes Explorer Units — they read existing definitions and precomputed results.

Find a dashboard

{
  "name": "search_terminal",
  "arguments": { "query": "stablecoin supply by chain", "limit": 5 }
}

Returns ranked hits with label, description, category, status, and URL. Set include_content: true with a small limit for the full rendered dashboard markdown. Never returns raw result rows or SQL.

List its charts

Call get_terminal_results with the dashboard_id and no chart_id to get the chart manifest.

Read a chart

{
  "name": "get_terminal_results",
  "arguments": {
    "dashboard_id": "<DASHBOARD_ID>",
    "chart_id": "<CHART_ID>",
    "mode": "both",
    "max_rows": 100
  }
}

mode is queries for SQL only, results for rows only, or both.

Terminal results are precomputed. Cite result.queried_at when you report values so the reader knows how fresh the numbers are, and link the reader to the Terminal dashboard itself — it carries context and visualizations the raw rows don’t.

A typical discovery flow

Check Terminal

search_terminal — is this already built? If yes, get_terminal_results for the SQL and use it as your baseline.

Find the tables

search_schemas with a descriptive query, then fetch the top table by id for full column detail.

Check the data model

search_docs for the vertical’s conventions — adjusted volume, decimals, re-org handling.

Load the SQL rules

get_skill(name="sql-optimization") before writing the query.

SQL & queries

Run the query once you’ve found the tables

Skills

Allium’s own guidance on writing efficient SQL

Data Catalog

The human-readable version of the schema catalog

Terminal

Browse the public dashboards yourself

Assistant

MCP

Machine Payments

Available tools

Search schemas

Search and browse documentation

Terminal dashboards

A typical discovery flow

SQL & queries

Skills

Data Catalog

Terminal

​Available tools

​Search schemas

​Search and browse documentation

​Terminal dashboards

​A typical discovery flow

​Related resources

SQL & queries

Skills

Data Catalog

Terminal

Available tools

Search schemas

Search and browse documentation

Terminal dashboards

A typical discovery flow

Related resources