mcp-crypto-toolkit
Server Details
Live crypto prices, conversion, gas tracker, portfolio tools, and calculators for AI agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- nad33mahm3d/mcp-crypto-toolkit
- GitHub Stars
- 0
Available Tools
10 toolscompare_coinsAInspect
Compare 2–5 cryptocurrencies side by side (price, mcap, volume, 24h change).
| Name | Required | Description | Default |
|---|---|---|---|
| coins | Yes | Array or comma-separated list, e.g. btc,eth,sol | |
| vs_currency | No | usd |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure; it does disclose the comparison scope and metric set. However, it says nothing about output format, data source/freshness, or behavior on invalid coin identifiers, leaving a gap for a first-time agent.
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?
One concise, front-loaded sentence. Every word contributes: action, range, resource, and comparison dimensions. No filler or schema repetition.
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 simple two-parameter read-only comparison tool, the description covers the main action and metrics, but with no annotations and no output schema it leaves unspecified the return shape and how vs_currency affects the comparison. An agent could probably call it correctly, but not with full confidence about the response.
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 description adds a useful constraint (2–5 coins) beyond the schema's 'Array or comma-separated list' example, but it does not explain the vs_currency parameter, whose schema description is missing. Because schema coverage is only 50%, the description should have provided at least some semantic contribution for the un-described parameter.
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?
Clearly states a specific action ('Compare') and resource ('cryptocurrencies'), with precise comparison metrics (price, mcap, volume, 24h change) and a 2–5 count constraint. This distinguishes it from siblings like get_price or top_coins without needing schema details.
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 phrase 'Compare 2–5 cryptocurrencies side by side' implies the intended use case of multi-asset comparison, but the description never explicitly states when to use it instead of convert, get_price, or top_coins, nor any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convertCInspect
Convert crypto amount to fiat/crypto. Optimized PKR via Binance P2P when requested.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | usd, eur, pkr, btc, eth, etc | |
| from | Yes | ||
| amount | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals one behavioral trait—PKR conversions may be optimized via Binance P2P—but does not explain rate sources, whether live data is fetched, how output is formatted, or whether any side effects occur. This is insufficient for an agent to predict the tool's runtime behavior accurately.
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 concise and front-loaded with the core action, followed by a brief optimization note. Every sentence carries some information, and there is no redundant filler. However, the second sentence is somewhat cryptic and could have been clearer, which slightly reduces its structural effectiveness.
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 the absence of an output schema and sparse parameter documentation, the description does not provide enough context for correct invocation. It omits the return format, the meaning of 'optimized', how rates are determined, and any constraints on the 'from' or 'to' values. An agent would need to make assumptions or query additional tools to use it reliably.
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 only 33%, so the description must compensate for the undocumented 'from' and 'amount' parameters. It adds some context by implying the input amount is a crypto amount and 'from' is likely a cryptocurrency, but it does not clarify accepted formats, units, or the exact meaning of the 'to' values beyond the schema's short list. The PKR optimization adds slight meaning to 'to' but remains underspecified.
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 clear action—'Convert crypto amount to fiat/crypto'—with a specific resource (crypto amount) and a notable optimization ('Optimized PKR via Binance P2P'). It distinguishes itself from siblings like get_price or compare_coins, though it does not fully elaborate on whether fiat-to-crypto or crypto-to-crypto conversions are also supported. Overall, it is specific enough to avoid being a tautology.
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 gives no explicit guidance on when to use this tool versus alternatives such as get_price or portfolio_value. It only hints at a special PKR path via Binance P2P, but never states the conditions that trigger this optimization or when a user should prefer this tool over another. The agent is left to infer use cases from the name and short description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gas_trackerBInspect
Live gas fees for EVM chains (eth, bnb, polygon, arbitrum, base, optimism) with estimated transfer cost in native + USD.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | eth |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden of behavioral disclosure. It does convey that data is live/current and that output includes native and USD estimates. However, it omits details such as update frequency, units for gas fees, what transaction is assumed for the transfer cost, and possible network-specific behavior.
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 a single, information-dense sentence with no filler. It front-loads the core function, then specifies supported chains and output format. Every element earns its place, and nothing needs to be trimmed.
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 tool with one optional parameter and no output schema, the description is largely sufficient: it states the domain, supported chains, and output form. Minor gaps are the lack of exact gas-fee units and the absence of an explicit statement about the default chain, though the schema already documents the default.
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 only parameter chain is fully enumerated in the schema, and the description repeats the chain list while adding that these are EVM chains. This reinforces meaning but does not add substantial detail beyond the enum. The 'native + USD' mention clarifies expected output rather than the parameter semantics themselves.
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 identifies the tool as providing live gas fees for specific EVM chains plus an estimated transfer cost. It lacks an explicit verb like 'get' or 'fetch', but the intent is unambiguous. It distinguishes itself from the sibling price/portfolio/comparison tools by describing a distinct gas-fee function.
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 explains what the tool does but gives no guidance on when to use it versus alternatives. There is no mention of scenarios where another sibling would be more appropriate, and no exclusions or prerequisites. Usage must be inferred from the tool name and the generic gas-fee description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_priceAInspect
Get live price of any cryptocurrency in any fiat, with market cap, volume, rank, ATH/ATL. Uses CoinGecko.
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes | Coin id or symbol: btc, bitcoin, eth, sol, etc | |
| vs_currency | No | Fiat: usd, eur, pkr, inr, gbp, etc | usd |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose that the tool performs a live lookup via CoinGecko and returns several market data fields, which is useful. However, it does not mention rate limits, failure behavior, or response formatting, though those are less critical for a simple read-only price lookup.
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 a single sentence, front-loaded with the primary action and scope. Every phrase adds relevant information: the live price, fiat support, additional market fields, and the CoinGecko data source. There is no filler or redundancy.
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 simple two-parameter tool with a well-covered schema, the description provides enough context: what data is returned, which currencies are supported, and what external source is used. It does not explain ambiguous coin symbols or output shape, but these are minor given the tool's simplicity and the schema's clarity.
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 input schema already documents both parameters clearly with examples: coin accepts ids or symbols like btc/bitcoin, and vs_currency accepts fiat codes with a default of usd. Schema description coverage is 100%, so the description adds little beyond the general claim of 'any fiat' and does not meaningfully extend the schema's parameter explanations.
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 uses a specific verb ('Get') and resource ('live price of any cryptocurrency in any fiat') and lists additional returned data such as market cap, volume, rank, and ATH/ATL. It is clear and self-contained, though it does not explicitly differentiate itself from siblings like historical_price or convert beyond the word 'live'.
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 implies a current-price use case through 'live price' but never explicitly states when to use this tool versus siblings such as historical_price, convert, or compare_coins. There is no clear when-not guidance or alternative routing, so the agent must infer usage context from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
historical_priceCInspect
Historical price on a date (DD-MM-YYYY) with investment snapshot, or a range chart via days (1/7/30/90/365/max).
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes | ||
| date | No | DD-MM-YYYY for point-in-time | |
| days | No | Range chart: 1, 7, 14, 30, 90, 180, 365, or max | |
| investment | No | Hypothetical investment on the historical date | |
| vs_currency | No | usd |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It adds the key modal behavior: a point-in-time snapshot versus a range chart via the 'or' relationship, and mentions the investment snapshot. However, it does not describe response shape, error behavior, or what happens if both date and days are supplied.
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?
One compact sentence with the main resource and usage modes front-loaded. It is easily scannable, though the incomplete days list slightly reduces precision.
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?
At 60% schema coverage with no output schema or annotations, the description should explain the two modes' selection rules, defaults, and response expectations. It omits the required coin parameter, the meaning of vs_currency, and the mutual exclusivity of date versus days.
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 already documents date, days, and investment; the description adds no new meaning and actually lists a subset of valid days, omitting 14 and 180. It gives no help for the undocumented coin and vs_currency parameters.
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 ('historical price') with two explicit modes: a point-in-time date with investment snapshot, or a range chart by days. It is easily distinguishable from sibling get_price by the word 'historical,' though it does not name the alternative.
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?
No guidance is given on when to use this tool instead of get_price or other siblings. The historical prefix only implies the use case, and there are no conditions or exclusions for choosing between the date and days modes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
portfolio_valueAInspect
Value a portfolio of holdings in any fiat (batch pricing). Pass [{coin, amount}, ...].
| Name | Required | Description | Default |
|---|---|---|---|
| holdings | Yes | ||
| vs_currency | No | usd |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It states the core behavior (portfolio valuation), the batch nature, and fiat support, but it does not disclose the return shape, behavior on unknown coins, or any failure/error semantics. This is a reasonable but not thorough 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?
Two short sentences with no filler: the purpose and input format are front-loaded, and the example-like payload is more informative than longer prose would be. Every clause earns its place.
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 two-parameter tool with no output schema or annotations, the description gives enough to construct a basic call. It falls short on clarifying what the result looks like (total value vs per-coin breakdown, currency symbol) and edge cases like unsupported coins, so an agent may need to infer the output contract.
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 0%, but the description partially compensates by showing the exact holdings shape as [{coin, amount}, ...] and referencing fiat conversion. It does not name vs_currency, define the coin identifier format, or specify amount units, leaving part of the meaning to the raw schema.
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 uses a specific verb ('Value') with a clear resource ('a portfolio of holdings') and adds the distinguishing trait 'batch pricing,' which separates it from single-coin siblings like get_price or convert. The input shape is given immediately, so there is no ambiguity about what the tool does.
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 phrase 'batch pricing' implies this tool is for valuing multiple holdings at once, and 'any fiat' sets the currency context. However, it does not explicitly state when to prefer this over sibling tools such as get_price, convert, or profit_calc, nor does it mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
profit_calcBInspect
Calculate crypto profit/loss, ROI, break-even. Supports exchange fees and fixed network/gas fee. No API needed.
| Name | Required | Description | Default |
|---|---|---|---|
| quantity | Yes | ||
| buy_price | Yes | ||
| sell_price | Yes | ||
| network_fee | No | Fixed network fee in same unit as prices | |
| buy_fee_percent | No | ||
| sell_fee_percent | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It usefully states that this is a self-contained calculation ('No API needed') and that it accounts for fees, but it does not disclose output shape, rounding, or how fees are applied.
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?
Three short sentences front-load the core function and add the most useful details with no filler. Every sentence earns its place.
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 six-parameter tool with no output schema and minimal schema descriptions, the description is too thin. It omits the expected return values, percentage-fee conventions, and how network fees interact with profit calculations.
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 only 17%, so the description must compensate. It names exchange fees and network/gas fees, which map to the optional params, but it leaves buy_fee_percent and sell_fee_percent units unclear and does not explain the required parameters beyond their names.
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 uses a specific verb and resource: 'Calculate crypto profit/loss, ROI, break-even.' This clearly differentiates it from sibling tools like get_price, convert, and portfolio_value, which address different tasks.
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?
No guidance is given about when to choose this tool over siblings or when not to use it. 'No API needed' hints at scope but does not state alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_coinAInspect
Search cryptocurrencies by name or symbol. Returns CoinGecko ids for use in other tools.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses the return concept (CoinGecko ids), but omits details like matching behavior, result ordering, limit enforcement, and pagination. 'Search' implies a safe read operation, and the return purpose is useful, but more transparency would help.
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?
Two concise sentences deliver the essential information with no filler. The action is front-loaded, and the follow-up sentence clarifies the tool's role in a broader workflow.
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 simple two-parameter search with no output schema and no annotations, the description covers the core purpose and main parameter. However, it omits what 'limit' does, how results are matched/ordered, and what the exact return payload looks like beyond 'CoinGecko ids'. These gaps make it only minimally complete.
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 0%, so the description must compensate. It explains that 'query' accepts a name or symbol, which is meaningful. However, the optional 'limit' parameter is not described at all, leaving its meaning and effect undocumented. Partial compensation keeps it at the baseline.
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 specific action ('Search cryptocurrencies'), the target resource ('cryptocurrencies'), the search dimensions ('by name or symbol'), and the result purpose ('Returns CoinGecko ids for use in other tools'). This clearly differentiates it from sibling tools focused on pricing, conversion, portfolios, and top/trending lists.
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 phrase 'for use in other tools' gives the agent a clear situational signal: this is a lookup/prerequisite step before using other CoinGecko-dependent tools. It does not explicitly name alternatives or when-not-to-use, but the context is strong enough to route the agent correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
top_coinsBInspect
Top cryptocurrencies by market cap or volume, with gainers/losers among the result set.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| order | No | market_cap_desc | |
| vs_currency | No | usd |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full behavioral disclosure burden. It does reveal a useful behavioral trait beyond the schema: the returned set includes gainers/losers. However, it does not describe the response item shape, whether gainers/losers are separate groupings or computed fields, or other runtime behavior such as defaulting or currency handling.
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 a single, front-loaded sentence with no filler. It states the core purpose first, then the ordering dimensions, then the gainers/losers feature. Every part earns its place.
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 no output schema and no annotations, the description should explain what the result list contains or how 'gainers/losers' is represented. It does not specify the response shape, the effect of `vs_currency`, or how the result set is structured. The sibling-tool list is present but not used in the description to clarify boundaries, leaving the definition below the minimum for confident invocation.
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 0%, so the description must compensate. It adds some meaning for the `order` parameter by mentioning 'market cap or volume' and hints at limiting via 'top', but it never explains `vs_currency`, and it does not explicitly clarify that `limit` controls the number of results. The schema's enum values and defaults help, but the description only partially covers the parameters.
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 the resource ('cryptocurrencies') and the selection criteria ('top by market cap or volume'), and adds a distinguishing feature ('gainers/losers among the result set'). It is clear that this is a market-ranking/list tool, unlike `get_price` or `search_coin`, though it does not explicitly call out sibling differences.
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 intended use case is implied: users wanting top coins ranked by market cap or volume, or looking at gainers/losers within that set. However, there is no explicit guidance about when to choose this over `trending`, `compare_coins`, or `search_coin`, and no 'use when / use instead' exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trendingBInspect
What's hot right now: CoinGecko trending coins plus Crypto Fear & Greed Index.
| Name | Required | Description | Default |
|---|---|---|---|
| include_fear_greed | No | Include Alternative.me Fear & Greed Index (default true) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the main output contents: CoinGecko trending coins and the Alternative.me Fear & Greed Index. With no annotations, the description must carry the behavioral transparency burden, but it does not mention output shape, pagination, freshness, or any side-effect profile, leaving notable gaps.
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 a single front-loaded sentence with no wasted words. It efficiently conveys the current-trend context and the exact payload sources in a compact, scannable form.
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 tool with one optional parameter, this is close to sufficient, but there is no output schema and no annotation context, so the description should specify more about the response shape or how include_fear_greed changes the result. It states the broad contents but leaves ambiguity about what 'trending coins' actually returns.
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 include_fear_greed parameter is already fully documented. The description only reinforces that the Fear & Greed Index is part of the result and does not clarify parameter effects or add meaningful semantic detail beyond the schema.
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 identifies the resource: CoinGecko trending coins plus the Crypto Fear & Greed Index, and 'What's hot right now' signals a current-market snapshot. However, it lacks an explicit verb like 'get' or 'list' and does not explicitly distinguish itself from siblings such as top_coins.
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?
No guidance is provided about when to use this tool versus alternatives like top_coins or get_price. The phrase 'What's hot right now' implies a current-trend use case, but there are no explicit exclusions, prerequisites, or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
10 tool updates
- First observed
compare_coins - First observed
convert - First observed
gas_tracker - First observed
get_price - First observed
historical_price - First observed
portfolio_value - First observed
profit_calc - First observed
search_coin - First observed
top_coins - First observed
trending
Frequently Asked Questions
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, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon 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.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
Loan & mortgage calculator, compound interest, ROI, crypto prices, FX conversion for AI agents.
Open API Marketplace for AI Agents. Crypto data tools with USDC payments on Base.
AI price forecasts, whale flows, market sentiment and prediction signals. 18 tools free, no account.
Crypto market signals and portfolio telemetry. 6 tools pay-per-call in USDC, no API key.
Related MCP Servers
- AlicenseAqualityCmaintenanceEnables AI agents to fetch live multi-chain portfolio, token info, gas prices, and token prices across Ethereum, Base, Polygon, Arbitrum, and Optimism with a single call. No API key required.4MIT
- FlicenseBqualityDmaintenanceEnables AI agents to interact with multiple blockchain networks to check wallet balances, gas prices, and transaction history on the Frax network. It also includes tools for real-time cryptocurrency conversion and sending automated notifications via Telegram.9-
- AlicenseAqualityCmaintenanceLive market data for AI agents. 8 tools: real-time crypto prices, OHLCV candles, order books, market cap rankings, trending coins, technical analysis (RSI/SMA/z-score), asset comparison, and Fear & Greed index. Zero API keys, zero dependencies.81MIT
- FlicenseNot gradedqualityDmaintenanceProvides real-time token pricing for AI models, model comparison, cost calculation, and token usage tracking for agents and developers.-
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Each tool targets a distinct action or use case: single price lookup, comparison, conversion, historical data, portfolio valuation, profit calculation, gas fees, search, top lists, and trending. Even get_price and compare_coins are clearly separated by single vs multi-coin scope.
Most tool names follow a clear, identifiable pattern with snake_case and intuitive operation+target naming like compare_coins, get_price, search_coin, and top_coins. A few deviations like convert, gas_tracker, and trending are still readable and not confusing.
Ten tools is well-scoped for a crypto toolkit. Each tool serves a meaningful standalone purpose and the count is neither bloated nor too thin.
The toolkit covers a broad range of crypto needs: pricing, comparisons, conversion, history, portfolio valuation, profit calculations, gas fees, top coins, and trending. Minor gaps exist around exchange-level data or detailed coin metadata, but the core surface is quite complete.