Skip to main content
Glama

airports

by io.github.pipeworx-io

Polymarket–Kalshi Spread

polymarket_kalshi_spread
Read-onlyIdempotent

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) topic — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit kalshi_event_ticker + polymarket_event_slug for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoPre-mapped: fed | btc | cpi | gdp | sp500 | recession | next_pope | next_uk_pm | next_israel_pm | 2028_president
kalshi_event_tickerNoExplicit Kalshi event ticker, e.g. "KXFED-26OCT". Overrides the topic-mapped Kalshi side.
polymarket_event_slugNoExplicit Polymarket event slug, e.g. "fed-decision-in-june-825". Overrides the topic-mapped Polymarket side.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "topic": "fed"
+  },
+  {
+    "topic": "btc"
+  }
+]
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description goes far beyond the readOnly/idempotent annotations by disclosing how matching works (keyword and word overlap, not a shared resolution source), the gross-vs-net fee caveat, the meaning of compatibility_codes, the fact that unclassified legs are never paired, and that temporal_alignment null means 'could not compute,' not 'aligned.' This is exceptional behavioral disclosure.

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 long, but dense with safety-critical details that are hard to convey in fewer words. It is well-structured with labeled sections (TWO MODES, RESPONSE, SAFETY FIELDS, Codes) and front-loads the core concept. A few redundancies exist, such as restating temporal alignment caveats in multiple places, but overall the length is justified by the tool's complexity.

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?

With no output schema, the description must carry the burden of explaining the return shape, and it does. It covers leg-by-leg prices, top_spreads_pp, compatibility_warning and codes, per-entry flags, skipped_unclassified, low_confidence_pairs, temporal_alignment, fees_note, and skipped counters. For a tool this intricate, the description is remarkably complete.

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 already documents all three parameters with descriptions and examples, giving 100% coverage. The description adds value by explaining that the explicit ticker and slug override the topic-mapped side, and that both modes run the identical matcher. This clarifies parameter interaction beyond the schema, though it does not transform understanding of any single parameter.

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 precise definition: 'Cross-venue spread between Kalshi and Polymarket for the same resolving question.' It clearly identifies the two venues, the object being compared (the same outcome), and the tool's role in computing the price delta. This strongly differentiates it from Polymarket-only siblings like polymarket_edges and polymarket_arbitrage.

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 explains the two invocation modes—pre-mapped topic shortcuts versus explicit ticker/slug pairings—and when each is appropriate. It also warns that pre-mapped topics often do not yield tradeable spreads. However, it does not explicitly name an alternative sibling tool for cases where the user should not use this tool, so it stops just short of full alternative routing.

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

All airports 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

A3.5/5.0
Disambiguation2/5

Many tools have distinct purposes, but the three 'ask_pipeworx' variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are highly similar and likely cause confusion. Additionally, the toolset mixes airport-specific tools with unrelated financial and research tools, creating ambiguity about when to use which.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use descriptive snake_case (ai_visibility_check, ask_pipeworx), others are single verbs (remember, forget, recall), and some include brand names (pipeworx_feedback). No clear pattern emerges across the 34 tools.

Tool Count1/5

34 tools is excessive for a server named 'airports'—only 3 tools directly relate to airports (search_airports, get_airport, calculate_distance). The majority are unrelated utilities (financial, prediction markets, memory), making the scope far too broad and unfocused.

Completeness1/5

The server severely lacks completeness for its stated airport domain: there are no tools for flights, airlines, runways, or real-time data. The other included domains (e.g., financial, prediction markets) are also incomplete, with e.g., only partial coverage of company data and no update/delete operations.

Resources