Real-time on-chain coordinated wallet detection for Solana tokens. Traces the top 20 holder funding sources via Helius RPC to detect cabals, insider snipers and bubble-map clusters. Returns a cabal confidence score 0–100. $0.05 USDC per query, paid natively on Solana. No API key, no account, no subscription.
Pre-trade safety check for any Solana token mint: is a buyer about to be someone's exit liquidity? Every flag links to its on-chain evidence tx.
AFTER YOU BUY: POST /api/watch {mint, webhook_url} with an X-API-Key (a free key is enough) and we push you an alert the moment a coordinated dump or liquidity drain starts on that token — carrying the same on-chain evidence. This scan is a BUY check; a watch is a HOLD check, and a holder needs the second one continuously. GET/DELETE /api/watch manage your own.
Layers, ordered by STRENGTH OF EVIDENCE (not marketing):
HOLDER CONCENTRATION — what share one wallet actually controls
(top_holder_pct). A single wallet that can crater the price is the
most basic rug vector, and it needs no coordination at all.
IMPORTANT: we count only REAL wallets. LP pools, locked/vesting supply
and other program-owned accounts are excluded and labelled, never scored
as a whale — and supply comes from getTokenSupply, not an estimate. Tools
that skip this report a locked-supply token as '65% one wallet'. Our
numbers reconcile with GMGN's circulating top-10.
SAME-BLOCK BUNDLES — holders whose token accounts were created in the
EXACT same block: a Jito-bundled multi-wallet launch. time_sync: true.
COORDINATED DUMP — ≥2 holders each selling ≥25% of their bag in the same
block: a cabal exiting in real time. coordinated_exit: true, sold_pct.
HONEYPOT / AUTHORITY TRAPS (Solana-native) — live freeze authority, un-revoked mint authority, Token-2022 transfer-fee / transfer-hook / permanent-delegate traps. Answers: CAN you actually sell this token?
DEV TRACK RECORD — the creator resolved on-chain plus their full launch history WITH the peak market cap each past token hit, so a dead-count can't hide a pump-and-dump. Covers ANY Solana venue: pump.fun, Raydium, Orca, Meteora, PumpSwap. A launch counts only where the transaction actually CREATED the mint, so re-minting supply of an existing token is never miscounted as a launch. reputation (SERIAL_RUGGER / DEAD_ON_ARRIVAL / MIXED / PROVEN) + best_peak_usd, pump_and_dumps count; paid tier adds launches[] (peak_mcap_usd, now_mcap_usd, drawdown, status per launch). 'Ran to $728k, now dust' = this dev has dumped six figures on holders before. Still CAPPED: peak history is evidence, never softens the score. READ deployer.verdict CAREFULLY — two values mean opposite things: FIRST_LAUNCH = we walked the history and found no earlier tokens. UNKNOWN = the history could NOT be established. That is not evidence of anything and must never be treated as a clean record.
FUNDING-CLUSTER TRACE — top holders walked back to a shared funding wallet. A real capability, listed last on purpose: on our own sample it produced no verified detections once infrastructure (curve PDAs, token accounts) was correctly excluded. Treat it as supporting evidence.
Returns risk (CLEAN|MEDIUM|HIGH), cabal_score 0–100, top_holder_pct, cluster
breakdown with evidence_txs[], holder map, deployer verdict, honeypot_risk,
plus wallets_checked / scan_complete / degraded so YOUR agent can apply its
own risk tolerance instead of inheriting ours. If we cannot verify something,
we say so (degraded: true) rather than returning a confident 'clean'.
COST: first 250 scans/month FREE — no signup, no API key. After that $0.001 USDC per scan. Every scan is a live on-chain trace, not cached data. Two ways to pay, no signup or card: (1) $9/month UNLIMITED (fair use, 50k/mo) — best for 24/7 bots; or prepaid pay-as-you-go at $0.001/scan (any amount) — POST the tx to /api/buy-key, then send header X-API-Key; or (2) per-call via x402 (X-Payment-Signature header). Full terms: GET /api/info.
Typical response time: <100ms for pre-indexed tokens (most graduated pump.fun mints are already cached). A token we have never seen runs the full live on-chain trace and takes 15-20s — set your client timeout to at least 30s or you will abandon a scan that was about to succeed.
| Name | Required | Description | Default |
|---|---|---|---|
| mintAddress | Yes | The Solana mint address of the token to audit (base58, 32–44 chars) | |
| pairCreatedAt | No | Optional: DexScreener pairCreatedAt timestamp in milliseconds. Speeds up analysis when provided. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and is unusually candid: it discloses live on-chain tracing, degraded-mode behavior ('we say so degraded: true rather than returning a confident clean'), evidence-linking, limitations of the funding-cluster layer, and response-time variance. It also explains the nuanced UNKNOWN vs FIRST_LAUNCH deployer verdicts and that past peak market caps never soften the risk score.
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 description is well organized with numbered evidence layers and bolded terms, but it is long and includes tangential API and payment details (watch endpoint, /api/buy-key, x402 payment, /api/info) that an MCP agent does not need in order to invoke this tool. The core purpose is front-loaded, but the overall message is not tight.
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?
Without an output schema, the description fully spells out what the agent receives: risk enum, cabal_score, top_holder_pct, evidence transactions, deployer verdict, honeypot risk, holder map, and degraded/completion flags. It also gives timeout guidance and cost thresholds, so the agent can invoke the tool with realistic expectations.
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 schema covers both parameters at 100%, so the baseline is 3. The description adds useful context about pre-indexed versus unseen tokens but does not materially extend the meaning of mintAddress or pairCreatedAt beyond what the schema already says.
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 opens with a precise statement of the tool: a pre-trade safety check on a Solana token mint to determine whether a buyer is about to become exit liquidity. It clearly names the resource, the action, and the output categories (risk, cabal_score, evidence), so an agent does not need to infer the purpose from the tool name.
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 description explicitly distinguishes this check from the /api/watch flow: 'This scan is a BUY check; a watch is a HOLD check, and a holder needs the second one continuously.' That tells an agent exactly when to invoke this tool versus set up a watch, and it also frames the tool as pre-trade rather than post-purchase.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Is a SPECIFIC wallet involved in a SPECIFIC Solana token? Use this when a user names a wallet they are worried about, or when your agent keeps its own watchlist of addresses and wants to screen a token against one.
Answers from two sources at once:
the traced holders of that token — rank, % of supply, buy slot, whether it funded a coordinated cluster, whether it created the token, or whether it is the liquidity pool / a labelled exchange wallet
a LIVE on-chain holding lookup, so a wallet too small to appear in the trace is still resolved rather than dismissed
HOW TO READ THE RESULT — this matters more than the fields:
found_in_scan=false is NOT a clean bill of health. The trace covers the
largest holders, so a smaller position sits outside it, and a wallet that
sold out and closed its token account leaves nothing to observe. Never
tell a user a wallet is 'clean' or 'not involved' on this result. The
note field states the limit of what was actually checked; relay it.
holding.sold_out=true is the strong signal: a token account exists holding none of the token, i.e. this wallet HELD it and has since sold out.
track_record, when present, counts earlier tokens the wallet was early in and how many graduated. It is an association measured out-of-sample, NOT a profit signal and not a recommendation to copy or avoid anyone. Absence of a track record means we hold no record, not that the wallet has no history.
Free, no API key, rate limited per caller. For screening MANY wallets on every scan automatically, the Screen List add-on stores a private list per key: POST /api/screen-list/checkout.
| Name | Required | Description | Default |
|---|---|---|---|
| wallet | Yes | The wallet address to look for in that token (base58, 32–44 chars) | |
| mintAddress | Yes | The Solana mint address of the token (base58, 32–44 chars) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so thoroughly. It discloses the dual-source lookup, warns that found_in_scan=false is not a clean bill of health, explains holding.sold_out=true as the strong signal, and cautions that track_record is not a profit signal or recommendation.
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 description is long but every section earns its place: purpose, behavior, result-interpretation caveats, and access constraints. It front-loads the core question and usage case, then structures critical warnings in a clear, readable way.
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?
Despite having no output schema and no annotations, the description covers what an agent needs to call and interpret the tool correctly: result meaning, limitations, false-negative risk, rate limiting, and authentication. Nothing essential appears missing for this tool's complexity.
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 schema already documents both parameters adequately. The description adds contextual meaning by framing them as 'specific wallet' and 'specific token,' but does not add meaningful semantic detail beyond what the schema provides.
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 clearly states the tool answers whether a specific wallet is involved in a specific Solana token, with a concrete use case. It does not explicitly differentiate itself from the sibling tool check_cabal_risk, so it misses the highest bar for sibling distinction.
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 explicit when-to-use guidance: when a user names a worried-about wallet or when an agent screens a token against a watchlist. It also mentions the Screen List add-on as an alternative for bulk screening, though it does not discuss exclusions relative to check_cabal_risk.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Add one secure layer between your agents and this server.
The two tools are clearly separated by focus: one evaluates a token's overall cabal/rug risk, while the other checks a specific wallet's involvement in a specific token. Their descriptions reinforce distinct use cases with no meaningful overlap.
Both tools follow the same snake_case verb-first convention: check_cabal_risk and check_wallet_in_token. The pattern is predictable and consistent, with no mixed casing or inconsistent verb styles.
Two tools is at the thin end of the range for a server with this broad-sounding purpose. However, each tool is substantive and earns its place; the count feels borderline rather than wasteful.
The pair covers token-level risk assessment and wallet-level involvement checks well, including honeypot, holder concentration, dev track record, and funding-cluster evidence. The main gap is that the watch/alert lifecycle is described as an external API rather than exposed as MCP tools, but agents can work around it using the provided endpoint details.