Skip to main content
Glama

Abn Lookup

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses important behaviors beyond the annotations: anonymous filing returns a claim_token, passing that token later retrieves resolution status, the endpoint is rate-limited to 5 per identifier per day, and it does not count against the tool-call quota. This gives the agent a clear model of side effects and limits without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place: purpose, use cases, exclusions, content guidance, token flow, rate limit, and cost. The most important guidance is front-loaded, and the caveats are grouped logically without redundancy.

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?

The description is complete for a feedback tool with no output schema. It tells the agent what to file, how to frame it, when not to file, what response token to expect, how to follow up, and what operational constraints apply. Nothing critical is missing for correct invocation.

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 description coverage is 100%, so the baseline is 3; the description adds genuine value on top by explaining the claim_token round-trip flow (file without account, get pwfb_ token, pass it back with no other arguments to read status) and by advising against pasting end-user prompts. It doesn't add much about the context object, but the schema already documents those fields well.

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 a concrete verb and object: "Tell the Pipeworx team something is broken, missing, or needs to exist." It then enumerates the exact feedback categories (bug, feature/data_gap, praise), making the tool's role unmistakable and clearly distinct from the research/lookup siblings.

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 gives explicit when-to-use conditions for each feedback type: wrong/stale data = bug, missing tool = feature/data_gap, positive experience = praise. It also gives a strong exclusion condition: feedback about tools from other MCP servers should be filed elsewhere, with a practical test for disambiguation based on the tool name source.

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

All Abn Lookup 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

A3.8/5.0
Disambiguation2/5

Several tools have unclear or overlapping boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, while ask_pipeworx, deep_research, and validate_claim all handle factual lookup/research tasks. The five polymarket_* tools plus bet_research also overlap enough that an agent could easily pick the wrong entry point despite verbose descriptions.

Naming Consistency3/5

All names are snake_case and generally descriptive, but conventions are mixed: some are verb-first (ask_pipeworx, resolve_entity, validate_claim), some are noun-first (abn_lookup, entity_profile, polymarket_edges), and prefixes like pipeworx_ and polymarket_ are used inconsistently. It is readable but not a clean, predictable pattern.

Tool Count2/5

34 tools is far too many for a server named 'Abn Lookup' — most of the surface is a broad data-research platform with prediction-market analysis, memory, subscriptions, feedback, and web utilities. The count could fit a large platform, but under this server name and with several near-duplicate entry points, it feels bloated.

Completeness4/5

For a read-only lookup/research server, coverage is strong: ABR lookups, entity resolution, single-query research, grounded verification, deep research, company profiles, comparisons, change feeds, prediction-market analysis, memory, and subscriptions are all represented. Minor gaps exist (e.g., no ACN search-by-name, no order execution), but no core workflow dead-ends.

Resources