Skip to main content
Glama

Wikidata

by io.github.pipeworx-io

Polymarket Arbitrage

polymarket_arbitrage
Read-onlyIdempotent

Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a trending_scan of the top ~200 markets by weekly volume; pass event for the strongest per-event partition_check, or topic for a themed cross-event scan. event (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). topic (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoSingle-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topicNoCross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

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?

Goes far beyond annotations: explains internal logic (monotonicity, partition checks), semantic anchor (Jaccard similarity), partition filter (placeholder slugs), fill check (realizable vs theoretical edge). No contradictions with 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?

Thorough but efficient; each sentence adds value. Structured with clear sections for each mode and response details. Slightly verbose in technical explanations but overall well-organized and front-loaded.

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?

Completely covers inputs, modes, internal checks, response structure, and limitations. No output schema, but description details the response fields and fill check logic. Perfectly adequate given complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage, but description adds significant meaning: explains event slug format with examples, topic mode behavior, cross-event scanning, and partition_check. Provides context not in 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: find arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes three modes (no args, event, topic) and contrasts with sibling polymarket_fill_risk.

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?

Explicit guidance: 'Call with NO args for a trending_scan', 'event (recommended for a specific market)', 'topic (for cross-event scanning)'. Also warns when not to trade based on fill check results and suggests polymarket_fill_risk for custom sizing.

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

All Wikidata 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

The tool set is extremely heterogeneous and overlapping. Multiple tools serve nearly identical purposes (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions), and entity-related tools (get_entity, get_wikidata_facts, entity_profile, compare_entities, resolve_entity) have unclear boundaries. The server is named Wikidata but only 3 of 34 tools actually relate to Wikidata, causing confusion about which tool is appropriate.

Naming Consistency2/5

Tool names mix multiple conventions: verb_noun (get_entity, search_entities, list_subscriptions), noun phrases (polymarket_edges, entity_profile, pipeworx_feedback), and inconsistent suffixes (_beta, _grounded). The verbs used are vague and not part of a coherent pattern (get, search, ask, discover, resolve, scan, validate, generate, remember, recall). The naming is readable but lacks a predictable system.

Tool Count2/5

34 tools is high for a server with a focused name like Wikidata, and nearly all tools belong to unrelated domains (Pipeworx data routing, Polymarket betting, memory management, subscriptions, AI visibility). The count appears bloated and scattered rather than well-scoped; most tools could be split into separate servers.

Completeness2/5

For a Wikidata server, the coverage is minimal: only search, get by ID, and human-readable facts are present, with no SPARQL query support or property-level access. The majority of tools address Pipeworx's broad data catalog, leaving the advertised Wikidata purpose severely under-served. The surface is complete for a different domain but incomplete for the stated one.

Resources