gapup-mcp

court_filings_multi

Read-only

Aggregate court filings, judgments and litigation records for a company or individual across five major legal jurisdictions: US (CourtListener / PACER), UK (National Archives — EWHC/EWCA/UKSC/UKUT), EU (ECHR HUDOC — European Court of Human Rights), France (Légifrance / Cour de cassation) and Germany (BGH / BVerfG). Returns structured case records with type classification (civil/criminal/antitrust/bankruptcy/administrative/unknown), status (filed/pending/decided/appealed/unknown), parties extracted from case titles, opinion URLs and verbatim snippets. Cross-case pattern recognition produces severity-ranked signals (P0–P2) for criminal, antitrust, bankruptcy, regulatory, data-breach and IP categories. Use when: due diligence on a counterparty, vendor risk assessment, competitive intelligence (litigation history), regulatory exposure mapping. All sources are public and keyless. Optional env var COURTLISTENER_API_KEY raises US rate limits beyond the default 5 req/s anonymous tier. SLA: ≤25s p95 (all jurisdictions fetched in parallel, 8s budget per source). Quality score: 20 pts per jurisdiction with ≥1 case retrieved, +10 if signals detected, +5–10 if ≥2–3 distinct sources contributed.

Input Schema

TableJSON Schema

Name	Required	Description
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`date_to`	No	ISO date YYYY-MM-DD — latest filing or decision date to include
`date_from`	No	ISO date YYYY-MM-DD — earliest filing or decision date to include
`party_name`	Yes	Name of the company or individual to search (e.g. "Apple Inc", "TotalEnergies", "Volkswagen AG")
`jurisdiction`	No	Jurisdictions to search. Defaults to all ["US","UK","EU","FR","DE"].

Output Schema

TableJSON Schema

Name	Required	Description	Default
`cases`	Yes
`status`	Yes
`signals`	Yes
`sources`	Yes
`party_name`	Yes
`quality_score`	Yes
`by_jurisdiction`	Yes
`jurisdictions_searched`	Yes

TDQS

A4.4/5.0

Behavior5/5

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

The description goes beyond annotations by detailing SLA (≤25s p95), quality scoring formula, optional rate limit key, parallel fetching strategy, and signal severity levels (P0–P2). Annotations already indicate read-only and non-destructive behavior, but the description adds operational transparency without 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 well-structured and informative, with clear front-loading of purpose and jurisdictions. It includes details on output, use cases, and SLA. While comprehensive, it is slightly verbose; each sentence adds value but could be tightened.

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's complexity (five jurisdictions, multiple data sources, cross-case pattern recognition, quality scoring) and the presence of an output schema, the description is sufficiently complete. It covers what, where, and how well the tool performs, leaving little ambiguity for an agent.

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?

Input schema coverage is 100%, so baseline is 3. The description adds context for jurisdictions (e.g., 'US (CourtListener / PACER)') but does not significantly elaborate on parameter usage beyond what the schema provides. Some parameter descriptions are in the schema already, so the added value is marginal.

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 aggregates court filings, judgments, and litigation records across five specific jurisdictions. It lists the data sources, what is returned, and cross-case pattern recognition. This differentiates it from sibling tools by specifying the multi-jurisdiction coverage and detailed outputs.

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?

The description explicitly provides use cases: due diligence, vendor risk assessment, competitive intelligence, regulatory exposure mapping. It notes all sources are public and keyless. However, it does not explicitly state when not to use this tool or mention specific alternative tools among the many siblings.

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

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TDQS

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

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