Skip to main content
Glama
Sign In

LuxAlgo MCP

by io.github.LuxAlgo
OverviewDiscussionsAdmin

Query a Market Trackers dataset

trackers_query
Read-only

Search one Market Trackers dataset by ticker, free text, exact field values, and event-date range, with paging and newest/oldest ordering. Data is read from year-sharded CC0 dumps: pass years (or since/until) to choose which years to read — default is the newest year with data. Deep-history years (see archiveYears in trackers_datasets) can be tens of MB compressed each, so read them one or two at a time; the tool refuses selections over its byte budget and says how to narrow. Every row carries provenance.sourceUrl (the SEC filing, disclosure, award, or record it came from). Examples: insider purchases at NVDA in 2024 → dataset insider-transactions, ticker NVDA, years [2024], where {code: 'P'}; a member of Congress's trades → congress-trades, text set to their name; who lobbied on a bill → lobbying-filings, text 'H.R.1234'.

Input Schema

NameRequiredDescriptionDefault
sortNoOrder by event date (default newest)
textNoCase-insensitive substring over the dataset's name/title fields (member, insider, issuer, recipient, registrant and client, sponsor, assignee, bill title, …); see textPaths in trackers_datasets
limitNoRows to return (default 25, max 100)
sinceNoEarliest event date (YYYY-MM-DD, YYYY-MM or YYYY), inclusive
untilNoLatest event date, inclusive
whereNoExact field matches by dot path, e.g. {"side":"buy"}, {"member.state":"CA"}, {"code":"P"}, {"formType":"4"}; string comparisons are case-insensitive, arrays match when any element does
yearsNoEvent years to read (max 8); default is the newest year with data. Prefer one year at a time for deep-history datasets.
offsetNoRows to skip, for paging (default 0)
tickerNoTrading symbol, case-insensitive (e.g. 'NVDA'); matches the dataset's ticker field(s). Only datasets flagged tickerSearchable carry tickers.
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
datasetYesDataset id, from trackers_datasets

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
    • addedInput schema / properties / offset / maximum
      Added value: +9007199254740991
    • removedInput schema / properties / until / $ref
      Removed value: -"#/properties/since"
    • addedInput schema / properties / until / pattern
      Added value: +"^\\d{4}(-\\d{2}(-\\d{2})?)?$"
    • addedInput schema / properties / until / type
      Added value: +"string"
    • addedInput schema / properties / where / propertyNames
      Added value: +{
+  "type": "string"
+}
  2. Added

TDQS

A4.2/5.0
Behavior5/5

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

With readOnlyHint/openWorldHint/destructiveHint already covering the safety profile, the description adds substantial non-obvious behavior: data comes from year-sharded CC0 dumps, the default year is the newest with data, deep-history years are tens of MB compressed, the tool self-limits via a byte budget and returns narrowing instructions on refusal, and every row carries provenance.sourceUrl. That is real operational context an agent cannot get from the schema.

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 purpose, the sharding/budget mechanics, and the examples are ordered sensibly with the core search capability front-loaded. The examples sentence is long and packs three scenarios into one breath, but each clause adds routing value rather than filler.

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

Completeness4/5

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

For an 11-parameter tool with no output schema, the description covers defaults, cost/limits, refusal behavior, and provenance fields well. It stops short of describing the row shape beyond provenance.sourceUrl, which is a minor gap given there is no output schema to lean on.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description goes beyond the schema by tying parameters together in end-to-end examples (dataset + ticker + years + where for insider purchases; dataset + text for lobbying) and by stating the default years behavior and the prefer-one-year-at-a-time rule for `years`.

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 opens with a precise verb+resource+capability statement: 'Search one Market Trackers dataset by ticker, free text, exact field values, and event-date range, with paging and newest/oldest ordering.' That cleanly separates it from a listing tool, but it never names the obvious siblings (trackers_datasets for discovery, trackers_latest, trackers_ticker), so the agent must infer the routing.

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?

Usage context is concrete: it explains the year-sharding model, that the default is the newest year with data, that deep-history years should be read 'one or two at a time', and it gives three worked examples mapping a user goal to dataset/ticker/years/where/text. What it lacks is explicit exclusion or alternative routing (when to prefer trackers_latest or trackers_ticker instead).

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

All LuxAlgo MCP toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources