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Glama

Eodhd

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and idempotentHint=true. Description adds that results include full input schemas with examples and are ready to call directly, which is valuable behavioral context beyond annotations. No contradictions.

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 front-loaded with the core purpose and usage guidance. It's moderately concise but includes a long list of example domains, which could be trimmed. Still well-structured.

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?

No output schema, but the description explains what is returned (names, descriptions, schemas, examples). Parameters are fully described with aliases and examples. Adequate for a discovery tool.

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

Parameters3/5

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

Schema coverage is 100% and description mentions aliases and provides examples. However, the description doesn't add critical meaning beyond what the schema already provides; the examples are helpful but not essential.

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

Purpose5/5

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

The description states 'Find tools by describing the data or task' with a specific verb and resource, and lists many example domains. It clearly distinguishes itself from sibling tools as the discovery entry point.

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

Usage Guidelines5/5

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

Explicitly says 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides clear when-to-use guidance and implies when not to use (when you already know the tool).

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

All Eodhd toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route research questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and bet_research all hunt prediction-market edges; ai_visibility_check and scan_competitor_ai_presence do nearly the same job. The verbose descriptions help, but an agent would still struggle to pick the right tool in these clusters.

Naming Consistency2/5

Everything is snake_case, but there is no coherent pattern: some names are verb_noun (compare_entities, validate_claim), some are bare verbs (remember, forget, recall), some are prefixed by domain (eodhd_*, pipeworx_*, polymarket_*, ai_visibility_*), and the Eodhd prefix clashes with the Pipeworx family. The conventions feel inherited from multiple unrelated codebases rather than a unified design.

Tool Count2/5

33 tools is already heavy for most servers, but the real problem is that only 2 tools (eodhd_eod_prices, eodhd_fundamentals) relate to the server's stated purpose. The other 31 span Pipeworx research, Polymarket betting, memory, subscriptions, feedback, llms.txt generation, and npm dependency checking — a massively over-scoped grab bag for a server named 'Eodhd'.

Completeness2/5

For the nominal EODHD domain the surface is severely incomplete: no splits, dividends, options, exchanges list, or other standard EODHD endpoints — just prices and fundamentals. As a general research/data platform it is broad rather than deep, mixing a decent question-answering core with unrelated one-off utilities, so no single coherent lifecycle is fully covered.

Resources