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Glama

Openchargemap

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").

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds significant behavioral details beyond annotations: fan-out to multiple sources, rate-limit handling (GDELT→GNews fallback), USPTO soft-fail due to API sunset, and return structure (changes grouped by source, total_changes count, pipeworx:// URIs). No contradiction.

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 somewhat long but well-structured, with clear sections for data sources, parameter details, and fallback behavior. Every sentence adds value, and it is not excessively verbose for the complexity of the tool.

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 complexity (three data sources, parameter details, fallback behavior) and lack of output schema, the description is remarkably complete. It explains what the tool returns (structured changes grouped by source, total_changes count, pipeworx:// URIs) and notes the patent soft-fail. No gaps.

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 baseline is 3. The description adds meaning: `type` is limited to 'company', `since` accepts ISO or relative shorthand with a recommended value ('30d' or '1m'), and `value` can be a ticker or CIK. This enhances understanding beyond the schema.

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 clearly states the tool's purpose as a change feed for a company over a recent time window, with explicit example queries and mention of data sources (SEC EDGAR, GDELT/GNews, USPTO). It differentiates from the sibling tool entity_profile, which is for static profiles.

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?

The description provides explicit usage examples (e.g., 'What's new with X') and gives guidance on when to use an alternative: 'Use entity_profile instead when you want the static profile'. It also explains fallback behavior and soft-fail conditions, offering clear context for tool selection.

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

All Openchargemap toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are nearly identical; Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) are hard to distinguish; memory tools (remember, recall, forget) and subscription tools (subscribe, unsubscribe, list_subscriptions, recent_alerts) also create ambiguity.

Naming Consistency2/5

Tool names mix snake_case (find_stations, get_station) with inconsistent verbs and noun phrases (ai_visibility_check, entity_profile, validate_claim). No clear pattern emerges, and some names are verbose or unclear (e.g., scan_competitor_ai_presence).

Tool Count2/5

At 33 tools, the set is too large for a focused server. Many tools are unrelated to the server name 'Openchargemap' (EV charging), and the collection feels like a grab bag of unrelated functionalities (Pipeworx data, Polymarket betting, AI visibility, memory management).

Completeness2/5

For the implied domain of EV charging, only two tools exist (find_stations, get_station), leaving major gaps (no CRUD). As a general utility, it lacks coverage in many areas (e.g., no file handling, no scheduling). The set is incomplete both as a domain-specific and general-purpose server.

Resources