Odds Api

Polymarket Edges

polymarket_edges

Read-onlyIdempotent

Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segment: (1) MODEL_DRIVEN — crypto_price (lognormal barrier from 90d FRED log-returns) and news_momentum (GDELT 7d/21d article-volume ratio, soft signal w/ halved Kelly). (2) STRUCTURAL_ARBITRAGE — partition_overround on mutually-exclusive events; per-leg favorite-longshot bias correction with per-sport α (tennis 1.02, soccer 1.10, MMA 1.15, default 1.0); placeholder-slug filter drops will-person-X / will-team-Y / will-manager-Z / will-someone-else- backstops; partitions with >20% placeholder fraction skipped entirely. (3) CONCENTRATED_LONGSHOT — basket trade when one leg ≥75% AND ≥2 longshots ≤8% AND portfolio return ≥25:1; rare-by-design (gates relaxed Run 8 from prior 85%/5%/50:1). EVERY OPPORTUNITY carries edge_pp_net (after slippage), kelly_fraction + kelly_fraction_half (capped at 0.25), market.liquidity, market.spread_pp, market.volume, plus a 24h-move warning ("Market moved X.Xpp in 24h") when the recent move alone exceeds the edge — your edge may already be in the price. TRADEABLE-EDGE KNOBS: min_liquidity / max_spread_pp drop opportunities where edge isn't realizable; min_partition_leg_kelly filters partitions by best per-leg Kelly. RESPONSE TOP-LEVEL: by_segment{model_driven,structural_arbitrage,concentrated_longshot}, fed_candidates/fed_note (Fed bets surface here, excluded from ranking — 1m-T vs EFFR signal is unreliable at meeting-month horizons without paid OIS/SOFR-futures data), and _diagnostics{concentrated_longshot:{...funnel counters},category_counts,filter_skips} so callers can see WHY a segment is empty (top-N stale, all candidates failed gates, knob dropped them). Cached 1h at the KV level keyed on all knobs.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Top N edges to return after ranking. Default 10, max 25.
`window`	No	Polymarket volume window to filter markets. Default 1wk.
`min_kelly`	No	Minimum half-Kelly fraction (as decimal, e.g. 0.005 = 0.5% of bankroll) to include single-leg opportunities. Default 0 (no filter). Skips opportunities that are too small to bet sensibly even if the edge is large.
`min_edge_pp`	No	Minimum \|edge\| in percentage points to include (default 0.5). Edge is evaluated NET of slippage.
`slippage_pp`	No	Assumed execution slippage in percentage points per leg (default 0.3). Subtracted from raw \|edge\| before ranking and Kelly sizing. Polymarket has zero trading fees as of 2024 but bid/ask + thin depth typically eats 20-50bp per trade. Bump for very thin partitions; drop to 0 if you have a smarter fill model.
`max_spread_pp`	No	Tradeable-edge filter. Maximum bid/ask spread in percentage points on the representative market. Default null (no filter). Set to 2 to require tight books — anything wider eats most plausible edges.
`min_liquidity`	No	Tradeable-edge filter. Minimum $ liquidity on the representative market (or for partition_overround, on at least one top_leg). Default 0 (no filter). Set to 5000 to drop thin-book opportunities where executing the edge would walk the book past breakeven.
`category_filter`	No	Comma-separated list to restrict the output: "model_driven" (crypto_price + news_momentum), "structural_arbitrage" (partition_overround), "concentrated_longshot". Combine like "model_driven,structural_arbitrage". Default: all.
`min_partition_leg_kelly`	No	Minimum BEST per-leg half-Kelly fraction across a partition_overround opportunity's top_legs (or longshot_basket legs). Default 0 (no filter). Partition arbs always return kelly_fraction_half=0 at the parent level by design (basket trades don't compose to single-leg Kelly), so min_kelly never filters them — this knob applies to the per-leg Kelly inside top_legs instead. Use to suppress thin partitions whose individual leg edges aren't worth the per-leg slippage cost.

Schema Changelog

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

Changed7 schema fields changedMay 27, 2026

addedInput schema / properties / category_filter

Added value: +{
+  "description": "Comma-separated list to restrict the output: \"model_driven\" (crypto_price + news_momentum), \"structural_arbitrage\" (partition_overround), \"concentrated_longshot\". Combine like \"model_driven,structural_arbitrage\". Default: all.",
+  "type": "string"
+}

addedInput schema / properties / max_spread_pp

Added value: +{
+  "description": "Tradeable-edge filter. Maximum bid/ask spread in percentage points on the representative market. Default null (no filter). Set to 2 to require tight books — anything wider eats most plausible edges.",
+  "type": "number"
+}

changedInput schema / properties / min_edge_pp / description

Previous value: -"Minimum |edge| in percentage points to include (default 0.5)."New value: +"Minimum |edge| in percentage points to include (default 0.5). Edge is evaluated NET of slippage."

addedInput schema / properties / min_kelly

Added value: +{
+  "description": "Minimum half-Kelly fraction (as decimal, e.g. 0.005 = 0.5% of bankroll) to include single-leg opportunities. Default 0 (no filter). Skips opportunities that are too small to bet sensibly even if the edge is large.",
+  "type": "number"
+}

addedInput schema / properties / min_liquidity

Added value: +{
+  "description": "Tradeable-edge filter. Minimum $ liquidity on the representative market (or for partition_overround, on at least one top_leg). Default 0 (no filter). Set to 5000 to drop thin-book opportunities where executing the edge would walk the book past breakeven.",
+  "type": "number"
+}

addedInput schema / properties / min_partition_leg_kelly

Added value: +{
+  "description": "Minimum BEST per-leg half-Kelly fraction across a partition_overround opportunity's top_legs (or longshot_basket legs). Default 0 (no filter). Partition arbs always return kelly_fraction_half=0 at the parent level by design (basket trades don't compose to single-leg Kelly), so min_kelly never filters them — this knob applies to the per-leg Kelly inside top_legs instead. Use to suppress thin partitions whose individual leg edges aren't worth the per-leg slippage cost.",
+  "type": "number"
+}

addedInput schema / properties / slippage_pp

Added value: +{
+  "description": "Assumed execution slippage in percentage points per leg (default 0.3). Subtracted from raw |edge| before ranking and Kelly sizing. Polymarket has zero trading fees as of 2024 but bid/ask + thin depth typically eats 20-50bp per trade. Bump for very thin partitions; drop to 0 if you have a smarter fill model.",
+  "type": "number"
+}

AddedMay 18, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations set readOnlyHint=true, etc. The description adds substantial behavioral context: caching (1h KV), response structure (by_segment with diagnostics), tradeable-edge knobs, model families, and per-opportunity fields. 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?

The description is well-structured with clear sections: opening purpose, model segments, knobs, response structure. It is front-loaded with the main purpose. However, it is somewhat verbose (over 600 words); could be more concise but the detail is valuable.

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 no output schema, the description thoroughly explains the return structure: top-level by_segment, per-opportunity fields, and diagnostics. It covers caching, edge calculation, and filters. For a complex tool with 9 parameters and multiple segments, the description is very 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?

Schema coverage is 100% with descriptions for all 9 parameters. The tool description adds extra context for some parameters (e.g., slippage_pp explains Polymarket fees, min_partition_leg_kelly explains its application), adding value 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 scans top Polymarket markets and returns opportunities where Pipeworx data disagrees with market price. It specifies the use case 'what should I bet on today' and distinguishes from sibling tools like polymarket_arbitrage by focusing on edge discovery without paging hundreds of markets.

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 says when to use: 'agents discover opportunities without paging hundreds of markets.' It details three segments and tradeable-edge knobs. It notes that Fed bets are excluded from ranking. However, it does not explicitly state when not to use this tool or provide direct comparisons with alternatives.

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

A3.5/5.0

Disambiguation2/5

Several tool clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same 5,724 tools with only subtle behavioral differences, and bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_kalshi_spread heavily overlap around prediction-market opportunity discovery. entity_profile, compare_entities, and recent_changes also fan out across the same SEC/news/patent sources, making selection ambiguous for agents.

Naming Consistency2/5

Naming mixes multiple conventions: snake_case verb_noun for odds tools (get_events, list_sports), vendor-prefixed clusters (ask_pipeworx_*, pipeworx_*, polymarket_*), and a few reversed noun-verb names like bet_research. CamelCase is used in ai_visibility_check and generate_llms_txt adds another style. Only the polymarket_* and pipeworx_* families are internally consistent, but the overall pattern is chaotic.

Tool Count2/5

37 tools is well beyond the typical well-scoped server, and the count feels inflated by unrelated meta-tools (suggest_questions, discover_tools, pipeworx_feedback, pipeworx_trending, generate_llms_txt, scan_dependency, remember/recall/forget) that have nothing to do with the server's stated 'Odds Api' purpose. The actual odds surface is only ~5 tools, so the vast majority of the catalog is off-scope padding.

Completeness3/5

The core odds domain is well covered: list_sports, get_events, get_odds, get_event_odds, and get_scores form a coherent lifecycle, plus quota introspection. However, for the server's actual broad-research scope there are noticeable gaps (e.g., no direct single-filing fetch tool despite heavy SEC coverage, a lone npm-dependency tool with no surrounding ecosystem, and no historical/past-odds endpoint), and the heterogeneous domains make completeness uneven.

Polymarket Edges

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

TDQS

Resources