Skip to main content
Glama

Podcastindex

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate read-only and idempotent behavior. The description adds substantial behavioral context: fans out to multiple sources (SEC, GDELT→GNews, USPTO with soft-fail), accepts ISO or relative dates, returns structured changes with URIs, and notes parallel execution. This goes well beyond annotations.

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 detailed but front-loaded with example queries that quickly convey purpose. Every sentence adds necessary information, though the length could be slightly trimmed. The structure is logical, starting with purpose, then behavior, then parameter tips, and ending with sibling distinction.

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

Completeness5/5

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

Given the tool has 3 required parameters and no output schema, the description thoroughly explains the return format (changes[] array, total_changes, citation URIs) and the multi-source behavior. It also covers edge cases like fallback and sunset. The agent can fully understand what to expect without additional documentation.

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?

The input schema has 100% description coverage, providing clear definitions for all three parameters. The description adds extra value by including examples for 'since' (e.g., "7d", "3m"), specifying that 'value' can be a ticker or CIK, and noting that 'type' is currently fixed to 'company'. This expands on the schema, though not massively.

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 opens with concrete example queries like "What's new with X" and clearly defines the tool as a change feed for a company over a time window. It explicitly distinguishes itself from the sibling tool 'entity_profile' by stating when to use the alternative.

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?

Provides explicit guidance on when to use this tool versus 'entity_profile' and gives a recommended default for the 'since' parameter ("30d" or "1m"). It also details fallback behavior and known limitations (PatentsView API sunset), helping the agent decide correctly.

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

All Podcastindex toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx and ask_pipeworx_grounded overlap (one is grounded), and bet_research/validate_claim/compare_entities/entity_profile all query Pipeworx data with different intents, which could cause confusion.

Naming Consistency4/5

Names are consistently lower_snake_case and mostly follow a verb_noun pattern (e.g., search_podcasts, get_podcast, list_subscriptions). A few compound names like pipeworx_feedback and polymarket_arbitrage deviate slightly but remain readable.

Tool Count2/5

30 tools is excessive for a server named 'Podcastindex'. It aggregates unrelated domains (podcasts, Pipeworx queries, Polymarket, memory, etc.), making it feel like a kitchen sink rather than a focused tool set.

Completeness3/5

For podcasts, the tool set covers search, metadata, episodes, and trending but lacks subscription management. For the broader Pipeworx domain, ask_pipeworx and discover_tools provide wide access, but specific gaps exist (e.g., no direct SEC filing query). Overall, the surface is broad but uneven.

Resources