Every pump.fun curve trade since 09-11: tape, launches, forensics, devs, odds + Meteora DLMM pools.
Scored across 12 tools
Each tool targets a distinct resource or analytic slice, and descriptions explicitly state scope boundaries with cross-references (e.g. pump_pulse vs pump_history for 'now vs trends', pump_wallet vs smart_money for 'one wallet vs leaderboard'). The only near-overlap (pump_token and pump_odds both take a mint) is resolved by pump_odds declaring itself 'for graduation probability only'. An agent can route cleanly without guessing.
The set uses a stable prefix_noun scheme with clear namespaces (pump_*, dlmm_*) that map to the two domains. The two cross-cutting analytics tools, copy_backtest and smart_money, break the prefix pattern but are still readable and unambiguous. Minor deviation only.
Twelve tools is well within the sweet spot and each one earns its place: market pulse, launches, token forensics, odds, dev, wallet, copy simulation, smart money, and three DLMM tools. No filler or redundant entries.
For the Pump & LP scope, coverage is strong: live and historical market stats, discovery, per-token forensics, graduation odds, creator track record, wallet performance, copy backtest, plus DLMM pool/positions/whales. Minor gaps remain, such as no way to list/discover DLMM pools by yield (only lookup by address) and no DLMM copy simulation, but core lifecycles are covered.
Would copying this wallet have made money? Replays its pump.fun entries and exits 0–25 slots late on the recorded curve and shows where the edge dies. Takes the wallet's pump.fun positions over the last 1–14 days and simulates a copier that buys the same token and sells when the leader sells, arriving 0, 1, 2, 5, 10 or 25 slots (0–10 s) late. Fills use the bonding-curve reserves our tape recorded at that moment, including curve fees and the copy's own price impact. Returns PnL, win rate and ROI per latency, the leader's own median ROI for contrast, and a verdict: copyable, latency-sensitive (edge gone by N slots), or not copyable. A wallet that looks great on its own PnL often loses money for anyone who follows it. When to use: After pump_wallet or smart_money, to check copying survives realistic delay. Price: $0.03 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | How many days of the wallet's history to replay. Range 1-14. Default 3. | |
| exit | No | sell on the leader's first sell, or once it has sold 90%. Default "first_sell". | first_sell |
| wallet | Yes | leader wallet to copy. Base58 Solana address, 32-44 chars. | |
| size_sol | No | SOL per copied entry. Range 0.01-10. Default 0.1. | |
| max_positions | No | most recent positions to replay. Range 10-300. Default 150. |
| Name | Required | Description |
|---|---|---|
| note | No | |
| found | No | |
| label | No | |
| setup | No | |
| by_lag | No | |
| wallet | No | |
| verdict | No | |
| fast_flips_pct | No | |
| biggest_at_2_slots | No | |
| leader_median_roi_pct | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well beyond the annotations (readOnly/idempotent/non-destructive): it discloses the fill model (bonding-curve reserves from the recorded tape, including curve fees and the copy's own price impact), the latency grid, the returned verdict categories, and pricing ($0.03/call, 10 free/day, x402 payment-required result). It also clarifies that upstream errors return isError and are not charged.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the core question and the mechanism, then layers simulation details, output, verdict, and operational notes (cost, errors). Dense but mostly non-redundant; the motivating line about wallets that look great on their own PnL earns its place as rationale, though the prose runs long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description need not explain returns, yet it summarizes PnL/win-rate/ROI per latency and the verdict anyway. Combined with cost, error behavior, and the when-to-use hook, nothing an agent needs to call it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so every parameter is already documented with ranges, defaults and the exit enum. The description reinforces the meaning ('last 1-14 days', 'sells when the leader sells') but adds no syntax or semantics beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource (replays a wallet's pump.fun entries/exits) and frames it with a concrete question ('Would copying this wallet have made money?'). It explicitly distinguishes itself from sibling tools by naming pump_wallet and smart_money as the upstream steps, so an agent can place it in the workflow without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'When to use: After pump_wallet or smart_money, to check copying survives realistic delay' gives both the trigger condition and the alternatives it complements. It also states cost and error semantics, leaving no routing or invocation ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
State of a Meteora DLMM pool: price, bin step, fees, TVL, volume and fees by window (30 m–24 h), 24 h fee yield and its annualized APR/APY. For LP agents choosing where to provide liquidity. When to use: For one pool's state; for a wallet's positions use dlmm_positions. Price: $0.002 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| pool | Yes | DLMM pool (pair) address. Base58 Solana address, 32-44 chars. |
| Name | Required | Description |
|---|---|---|
| fees | No | |
| name | No | |
| pool | No | |
| config | No | |
| volume | No | |
| apr_pct | No | |
| token_x | No | |
| token_y | No | |
| tvl_usd | No | |
| reserves | No | |
| created_at | No | |
| yield_note | No | |
| current_price | No | |
| fee_tvl_ratio | No | |
| dynamic_fee_pct | No | |
| fee_yield_24h_pct | No | |
| apy_pct_daily_compounding | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which already declare read-only/idempotent/open-world), the description discloses cost and quota behavior ($0.002 per call, 10 free/day, then an x402 payment-required result), and error semantics (isError with a message on invalid input or upstream failure, and that failures are not charged). These are operational traits an agent cannot obtain from the annotations or schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads what the tool returns, then usage, then pricing, then error behavior — a sensible priority order with no filler sentences. It is a dense single paragraph, but every clause carries information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanation is unnecessary, and the description still covers scope, sibling routing, pricing/quota, and error handling for a one-parameter tool. Nothing an agent needs to call this correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single 'pool' parameter is fully documented in the schema (base58 Solana address, 32-44 chars) plus a regex pattern. The description adds no format or syntax detail beyond that, so the schema does the heavy lifting — baseline 3 is correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific resource (Meteora DLMM pool state) and enumerates exactly which state fields are returned (price, bin step, fees, TVL, volume, fee yield, APR/APY), so an agent knows precisely what it gets. It also explicitly separates itself from the sibling dlmm_positions by scope (one pool vs a wallet's positions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives an explicit target audience ('For LP agents choosing where to provide liquidity') plus a when-to-use rule: 'For one pool's state; for a wallet's positions use dlmm_positions.' The alternative tool and the condition selecting it are named directly, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Open Meteora DLMM positions of any wallet: value, unclaimed fees, PnL, in/out of range — or its closed-position history. Set history=true for closed positions with deposits, withdrawals, fees and PnL per pool. When to use: For a wallet's Meteora positions; to find skilled LPs use dlmm_whales. Price: $0.005 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page of closed-position history (only with history=true). Range 1-50. Default 1. | |
| wallet | Yes | wallet address. Base58 Solana address, 32-44 chars. | |
| history | No | true = closed-position history instead of open positions. Default false. |
| Name | Required | Description |
|---|---|---|
| mode | No | |
| page | No | |
| pools | No | |
| total | No | |
| wallet | No | |
| has_next | No | |
| sol_price | No | |
| pools_total | No | |
| positions_total | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, open-world and non-destructive. The description adds substantial context beyond them: per-call pricing, a 10-free/day quota, an x402 payment-required fallback, and error semantics (isError on invalid input or upstream failure, and that failures are not charged). Gaps remain only around auth details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the core capability before cost and error notes, and every sentence carries information. It is dense, packing pricing, quota, routing and error handling into one paragraph, but nothing is filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need no explanation. The description covers the use case, the closed-position mode, cost/payment path and error behavior, which is everything an agent needs to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description meaningfully explains the history flag (closed positions with deposits, withdrawals, fees and PnL per pool), which adds semantic value beyond the schema's terse 'true = closed-position history'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific resource and scope: open Meteora DLMM positions for any wallet, enumerating returned data (value, unclaimed fees, PnL, in/out of range) and the closed-position variant. It explicitly distinguishes itself from the sibling dlmm_whales, so an agent can route correctly without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'When to use' clause names the exact scenario (a wallet's Meteora positions) and the alternative for the adjacent goal (find skilled LPs via dlmm_whales). It also states the condition (history=true) that selects the closed-position mode.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Meteora DLMM liquidity providers ranked by measured on-chain edge: net USD, median multiple, win rate, hold time, size, recency. Produced by our own discovery engine, which decodes DLMM liquidity instructions across high-volume and high-yield pools every few hours and scores each wallet's completed round trips. These are the wallets our live copier watches. Price: $0.02 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many ranked LP wallets to return. Range 1-25. Default 10. |
| Name | Required | Description |
|---|---|---|
| method | No | |
| whales | No | |
| generated_at | No | |
| pools_scanned | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the read-only/idempotent safety profile, and the description adds substantial context beyond them: data provenance (own discovery engine decoding DLMM instructions across high-volume/high-yield pools), refresh cadence (every few hours), cost model ($0.02/call, 10 free/day, x402 payment-required result), and error behavior (isError, not charged). This is exactly the extra behavioral context the bar rewards.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the identity and ranking criteria, then provenance, then pricing, then error handling. Dense but every sentence carries distinct information; slightly packed for a single paragraph but no wasted filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanation is unnecessary, and the description fills the remaining gaps an agent needs: cost/quota, failure semantics, data freshness, and the source of the ranking. Nothing required for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'limit' parameter, including default and 1-25 range, so the schema already carries full semantics. The description adds nothing about the parameter, which is the correct baseline when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource (Meteora DLMM liquidity providers) and spells out the ranking dimensions (net USD, median multiple, win rate, hold time, size, recency). An agent can distinguish it from dlmm_pool, dlmm_positions, and smart_money purely from the description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides useful context ('these are the wallets our live copier watches') that implies a copy-trading/discovery use case, and pricing guidance is explicit. However, it never states when to pick this over siblings like smart_money or dlmm_positions, nor any exclusions. Usage is implied rather than directed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
A creator wallet's launch history: launches, graduation rate, launch cadence, how fast the dev sells, verdict. Looks up every token the wallet created since recording began and replays the dev's own trades on its 15 most recent launches. When to use: For the creator of a token; pass the dev wallet, not the mint (pump_token reports the dev of a mint). Price: $0.01 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| creator | Yes | creator (dev) wallet. Base58 Solana address, 32-44 chars. |
| Name | Required | Description |
|---|---|---|
| found | No | |
| creator | No | |
| verdict | No | |
| baseline | No | |
| launches | No | |
| graduated | No | |
| last_launch | No | |
| first_launch | No | |
| recent_launches | No | |
| launches_last_24h | No | |
| graduation_rate_pct | No | |
| median_gap_between_launches_s | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, open-world, non-destructive, but the description adds behavior they cannot express: cost ($0.01 per call, 10 free/day, x402 payment-required result), error semantics (isError for invalid input or upstream failure, not charged), and the replay scope (15 most recent launches). That is meaningful disclosure beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is dense but front-loaded: the returned metrics come first, then usage, then cost, then error behavior. Every sentence carries information, though the run-on enumeration of metrics and the pricing/error clause make it longer than strictly necessary for a single-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description correctly focuses on routing, cost, and failure modes rather than return shape, and the annotations already carry the safety profile. Nothing an agent needs to invoke it or handle payment/error outcomes is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single well-documented 'creator' property (Base58 pattern, 32-44 chars), so the baseline is 3. The description goes slightly beyond the schema by stressing that this must be the dev wallet rather than the mint address, which disambiguates a common misuse.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (a creator wallet's launch history) and enumerates exactly what it computes: launches, graduation rate, launch cadence, dev sell speed, and a verdict. It also explicitly distinguishes itself from the closest sibling by stating 'pass the dev wallet, not the mint (pump_token reports the dev of a mint)', so an agent can route correctly without opening either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit 'When to use' clause scoped to the creator of a token, plus a negative instruction ('not the mint') and names the alternative tool that reports the dev of a mint (pump_token). This is precise when/when-not/alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pump.fun over time: launches, graduations, graduation rate, trades, SOL volume and unique wallets per day or hour since 2026-09-11 — with a compare window. The same tape as pump_pulse, sliced into UTC days or hours so an agent can compare the market over time instead of reading one snapshot. Pass compare_from/compare_to to get a second window and the per-period change (e.g. this week vs last week). Closed periods are precomputed from our own live recording of every bonding-curve trade; the open period is marked partial. Also reports the share of trades made by pump.fun's own mayhem agent, so it can be separated from real demand. When to use: For trends over days or hours; for the last 15 minutes use pump_pulse. Price: free. Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | UTC end, inclusive (default: now) | |
| from | No | UTC start, e.g. 2026-09-18 or 2026-09-18T06 (default: 14 days / 48 hours back) | |
| compare_to | No | end of the comparison window, inclusive | |
| granularity | No | Bucket size: "day" or "hour". Default "day". | day |
| compare_from | No | start of a second window to compare against |
| Name | Required | Description |
|---|---|---|
| rows | No | |
| compare | No | |
| summary | No | |
| coverage | No | |
| timezone | No | |
| definitions | No | |
| granularity | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds real behavioral context beyond them: closed periods are precomputed from the tool's own recording of bonding-curve trades, the open period is flagged partial, and a share of trades attributable to pump.fun's own mayhem agent is reported separately. It stops short of describing pagination/limits on the number of returned buckets.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with what it returns, then differentiation, compare semantics, provenance, usage and pricing in a logical order. Slightly long and a touch repetitive in restating the pump_pulse relationship, but every sentence carries information an agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values need no explanation, and defaults for from (14 days / 48 hours back) and to (now) are called out explicitly. Provenance, partial-period marking, comparison behavior, cost and error handling together make the definition complete for a 5-parameter, zero-required tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline would be 3. The description adds meaning beyond the schema by framing compare_from/compare_to as producing a second window plus a per-period change (e.g. this week vs last week), which the parameter descriptions alone do not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Names the specific resource (pump.fun metrics: launches, graduations, graduation rate, trades, SOL volume, unique wallets) and the slice it returns (per UTC day or hour) with an explicit compare window. It actively distinguishes itself from the sibling pump_pulse by describing itself as 'the same tape as pump_pulse, sliced into UTC days or hours' rather than a 15-minute snapshot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Contains an explicit 'When to use' clause: trends over days or hours here, last 15 minutes in pump_pulse. It also states cost ('Price: free') and error/charging behavior, leaving nothing about selection or prerequisites to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The newest pump.fun tokens with dev buy, early buyers/volume, curve progress, market cap and creator launch count. Returns up to 50 of the most recent launches (seconds old) with the first-N-seconds flow already aggregated, so an agent can shortlist without replaying the chain. When to use: To discover new mints; then use launch_scan (on the A.U.G.U.R Synapse · Wallets & Risk server, https://augur-trade.com/hub/mcp/risk) for a verdict on one of them. Price: $0.002 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many of the newest launches to return. Range 1-50. Default 20. | |
| window_s | No | early-flow window after creation. Range 30-3600. Default 300. |
| Name | Required | Description |
|---|---|---|
| launches | No | |
| window_s | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well beyond the annotations by disclosing the cost model ($0.002/call, 10 free/day, x402 options on payment-required results) and error semantics (isError with a message, not charged). It also explains that early flow is pre-aggregated so no chain replay is needed, which materially shapes how the agent uses the result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four compact sentences front-loaded with purpose, then the use case, then cost, then error behavior. Every sentence carries information an agent needs (pricing and error semantics are not optional for a paid tool).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanation is not required; the description still covers the key operational facts — freshness, result cap, cost, and failure behavior. Nothing needed to call this correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (limit, window_s) are already fully documented with ranges and defaults. The description alludes to the window conceptually ('first-N-seconds flow already aggregated') but adds no syntax or format detail beyond the schema — baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific resource (newest pump.fun tokens) and enumerates the returned fields (dev buy, early buyers/volume, curve progress, market cap, creator launch count), plus the freshness bound ('seconds old') and cap ('up to 50'). An agent can distinguish this discovery-listing tool from siblings like pump_history and pump_token.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'When to use: To discover new mints' with a concrete follow-on step routing to launch_scan for a verdict. It does not, however, say when to prefer a sibling such as pump_pulse or pump_history instead, so the alternative-selection guidance is only partially covered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Probability a pump.fun launch graduates, from how comparable launches in our tape actually ended — with the lift over the ~3% base rate. Buckets the launch's first 60 seconds (unique buyers, buy SOL, dev buy) and returns the empirical graduation rate of thousands of comparable recent launches whose outcome is known, shrunk toward coarser buckets when samples are thin. Rebuilt every 6 hours. When to use: For graduation probability only; launch_scan (on the A.U.G.U.R Synapse · Wallets & Risk server, https://augur-trade.com/hub/mcp/risk) includes it alongside the other checks. Price: $0.01 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | pump.fun token mint. Base58 Solana address, 32-44 chars. |
| Name | Required | Description |
|---|---|---|
| mint | No | |
| age_s | No | |
| found | No | |
| model | No | |
| method | No | |
| status | No | |
| symbol | No | |
| swap_url | No | |
| created_at | No | |
| graduation | No | |
| launch_minute | No | |
| curve_progress_pct | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well past the readOnly/idempotent/openWorld annotations: discloses the bucketing methodology (first 60s of unique buyers, buy SOL, dev buy), shrinkage toward coarser buckets under thin samples, a 6-hour rebuild cadence that implies staleness, pricing ($0.01/call, 10 free/day, x402 payment-required result), and error semantics (isError with message, not charged). This is unusually rich operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core answer and method, then cleanly segmented into 'When to use', 'Price', and 'Errors'. The opening sentence is clause-heavy (em-dash aside plus a secondary explanation), but nearly every sentence carries decision-relevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present the description need not describe return shapes, and it doesn't try to. It covers everything an agent needs to select and invoke correctly: methodology, refresh cadence, cost, error behavior, and the boundary against the sibling that bundles this check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the single 'mint' parameter is fully documented in the schema, including base58 format and length constraints. The description adds no parameter-level detail beyond what the schema already conveys, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a precise verb+resource+scope: the probability that a specific pump.fun launch graduates, computed empirically from comparable historical launches and expressed as a lift over the ~3% base rate. This is clearly distinguishable from siblings like pump_token, pump_launches, and pump_pulse, which the agent can rule out without opening any schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly bounds itself: 'For graduation probability only', then names the alternative (launch_scan on the A.U.G.U.R Synapse · Wallets & Risk server) and clarifies that the sibling bundles this check with others. It also states the cost model and free tier, which is a real selection factor.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Live pump.fun heartbeat: trades/min, launches, graduations, graduation rate, hottest tokens in the last 15 min. Computed from our own live recording of every pump.fun bonding-curve trade. Use it to decide whether the launch market is hot or dead before scanning individual tokens. When to use: For the market right now; for trends over days use pump_history. Price: free. Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| as_of | No | |
| sol_usd | No | |
| coverage | No | |
| last_24h | No | |
| last_hour | No | |
| hottest_15m | No | |
| trades_per_min | No | |
| recent_graduations | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds value beyond them: cost ('Price: free'), error behavior ('returns isError ... not charged'), and data provenance from live recording. This is behavioral context an agent cannot get from the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core purpose, then data scope, then usage routing, then price and error semantics. Every sentence carries information (metrics, provenance, routing, cost, failure mode) with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, yet the description still lists the headline metrics. Combined with cost and error disclosure for a zero-param read tool, nothing an agent needs to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes no parameters, so there is nothing to document and the baseline is 4. The description correctly does not invent parameter semantics; it instead enumerates the output metrics, which is appropriate for a zero-arg tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a concrete verb and resource: a live market heartbeat with named metrics (trades/min, launches, graduations, graduation rate, hot tokens over 15 min). It also discloses the data source ('our own live recording of every pump.fun bonding-curve trade'), which distinguishes it from siblings like pump_history and pump_launches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit routing: 'Use it to decide whether the launch market is hot or dead before scanning individual tokens' and 'When to use: For the market right now; for trends over days use pump_history.' Names both the situation and the alternative, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Full bonding-curve forensics for one pump.fun mint: flow, dev buys/sells, launch snipers, top curve holders, peak, graduation, red flags. Aggregates every recorded curve trade of the token: unique wallets, buy/sell SOL, first-60-second flow, whether the dev sold out, non-dev wallets that bought in the launch slots (bundles), top net holders on the curve, peak market cap and post-graduation liquidity. When to use: For raw curve forensics on one mint. For a single scored verdict use launch_scan (on the A.U.G.U.R Synapse · Wallets & Risk server, https://augur-trade.com/hub/mcp/risk); for a contract/liquidity safety grade (also after graduation) use token_risk (on the A.U.G.U.R Synapse · Wallets & Risk server, https://augur-trade.com/hub/mcp/risk); for the creator's track record use pump_dev. Price: $0.01 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | pump.fun token mint. Base58 Solana address, 32-44 chars. |
| Name | Required | Description |
|---|---|---|
| dev | No | |
| flow | No | |
| mint | No | |
| name | No | |
| note | No | |
| curve | No | |
| flags | No | |
| found | No | |
| mayhem | No | |
| symbol | No | |
| creator | No | |
| socials | No | |
| swap_url | No | |
| first_60s | No | |
| created_at | No | |
| token_program | No | |
| launch_snipers | No | |
| post_graduation | No | |
| top_curve_holders | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive/openWorld, but the description goes further with cost ($0.01/call, 10 free/day, x402 payment-required result) and error semantics (isError on invalid input or upstream failure, not charged). These are operational traits the annotations cannot express.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Dense but front-loaded: the forensic scope leads, then usage routing, pricing, and errors. The long enumeration of aggregates is list-like, but every item distinguishes what the tool returns, so little is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists so return values need no explanation, and the description still covers scope, alternatives, cost, and failure behavior. An agent has everything needed to select and call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With one parameter at 100% schema coverage, the schema fully documents the mint address and its base58 pattern. The description reinforces the scope ('one pump.fun mint') and the single-mint granularity, adding light value beyond the schema without inventing syntax.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource (bonding-curve forensics for one pump.fun mint) and enumerates the exact aggregates returned (flow, snipers, top curve holders, peak, graduation). It differentiates from siblings by naming launch_scan, token_risk, and pump_dev with their distinct scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'When to use' clause plus a routing table: use this tool for raw curve forensics, launch_scan for a scored verdict, token_risk for contract/liquidity safety, pump_dev for creator track record. Alternatives are named with their servers and URLs, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Any wallet's pump.fun trading record: realized PnL, win rate, hold time, frequency (bot or human), tokens it launched. Analyses up to the last 20,000 curve trades of the wallet. Use it to judge whether a wallet is smart money, a sniper bot, a serial dumper or a dev. When to use: For a trader's pump.fun performance. For a quick deal/no-deal verdict on any wallet use counterparty_check (on the A.U.G.U.R Synapse · Wallets & Risk server, https://augur-trade.com/hub/mcp/risk); to test whether copying it pays use copy_backtest. Price: $0.01 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many of the wallet's most recent recorded trades to analyse. Range 100-20000. Default 20000. | |
| wallet | Yes | wallet address. Base58 Solana address, 32-44 chars. |
| Name | Required | Description |
|---|---|---|
| note | No | |
| found | No | |
| label | No | |
| wallet | No | |
| window | No | |
| activity | No | |
| recent_tokens | No | |
| classification | No | |
| created_tokens | No | |
| closed_positions | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds substantial operational context: the 20,000 curve-trade analysis cap, $0.01 per call pricing, a 10 free/day quota, a payment-required result listing x402 options, and that isError responses for invalid input or upstream failure are not charged. The only missing piece is anything about result shape or latency, which the output schema covers.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Dense but well front-loaded: purpose first, then scope, then when-to-use and alternatives, then pricing and error semantics. Every sentence carries information, though the paragraph is long enough that a reader must scan multiple clauses to find the pricing and error facts.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only analytical tool with only two parameters, an output schema that covers return values, and full annotation coverage, the description supplies everything else an agent needs: scope, alternatives, cost model, quota, and failure semantics. Nothing material is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are already fully documented, making 3 the baseline. The description's mention that analysis covers 'the last 20,000 curve trades' adds a modest qualifier about what the limit actually counts, but it does not exceed the schema materially.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Any wallet's pump.fun trading record') and enumerates the exact outputs (realized PnL, win rate, hold time, bot/human classification, launched tokens). It is clearly distinguishable from siblings like pump_dev, pump_token and smart_money because it is a per-wallet performance profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use it ('For a trader's pump.fun performance') and names two alternatives with the conditions that select them: counterparty_check for a quick deal/no-deal verdict, copy_backtest to test whether copying pays. The named alternative even carries a server/URL reference, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The pump.fun wallets with the best realized PnL in the last 24 h — and the tokens those wallets are buying right now. Leaderboard of wallets by realized profit on fully-closed curve positions (min 8 closed, rebuilt every 30 min), sortable by PnL, win rate or ROI, plus a live feed of what the top 50 bought in the last N minutes, ranked by how many of them piled in. When to use: To find wallets worth watching; then copy_backtest to test copying one. Price: $0.02 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Rank by realized PnL in SOL ("pnl"), win rate ("win_rate") or return on SOL spent ("roi"). Default "pnl". | pnl |
| limit | No | How many top wallets to return. Range 1-50. Default 20. | |
| window_min | No | look-back for buying_now. Range 1-120. Default 15. | |
| exclude_bots | No | drop sub-20-second and high-frequency wallets. Default false. |
| Name | Required | Description |
|---|---|---|
| note | No | |
| sort | No | |
| window | No | |
| wallets | No | |
| buying_now | No | |
| leaderboard_built_at | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive, but the description goes well beyond by disclosing the $0.02-per-call price, the 10 free/day quota, the x402 payment-required path, the 30-minute rebuild cadence, and that invalid input or upstream failures return isError uncharged. It does not, however, describe the freshness/latency of the live feed beyond the window parameter. Strong 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The core output is front-loaded in the first sentence before the sortable/feed details, and the when-to-use, price, and error clauses are ordered usefully. It is dense and multi-clause, but nearly every clause adds a distinct fact rather than padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values need not be re-explained, and the description still covers pricing, quota, error behavior, refresh cadence, ranking basis, and the natural follow-up tool. Nothing an agent needs to call it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline would be 3, but the description adds meaning by tying window_min to the buying_now feed ('last N minutes'), limit to the leaderboard ('top 50'), and sort to PnL/win-rate/ROI. It clarifies which param drives which half of the response, which the schema alone does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise verb+resource (a wallet leaderboard ranked by realized PnL plus a live buying feed) and immediately scopes it: 'fully-closed curve positions (min 8 closed, rebuilt every 30 min)'. It is clearly distinguishable from siblings like pump_wallet and copy_backtest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit when-to-use ('To find wallets worth watching') and routes the agent to the next step with a named alternative ('then copy_backtest to test copying one'). Nothing about tool selection is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
copy_backtestdlmm_pooldlmm_positionsdlmm_whalespump_devpump_historypump_launchespump_oddspump_pulsepump_tokenpump_walletsmart_moneySolana + pump.fun intel for agents: launch verdicts, token risk, dev/wallet records, smart money.
Who is behind a launch: bundles, insiders, airdrops, serial devs. Solana pump.fun + 18 EVM chains.
Dev records, pump.fun + Robinhood Chain: launches, rugs, bonded, live last mint. Every figure has N.
Solana DeFi MCP: Meteora DLMM brief+detail; Solana DEX scout. Commerce optional.
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