crypto-feargreed-mcp
Offers cryptocurrency market sentiment analysis through the Fear & Greed Index, providing tools for interpreting market conditions specifically for Bitcoin trading and investment decisions.
Enables installation and distribution of the Crypto Fear & Greed Index MCP server through GitHub repositories, allowing users to clone and deploy the server from the GitHub platform.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@crypto-feargreed-mcpshow me the current Crypto Fear & Greed Index"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Crypto Fear & Greed Index MCP Server
A mcp server that provides real-time and historical Crypto Fear & Greed Index data, powered by the Alternative.me.
This server exposes resources and tools for fetching and analyzing the Fear & Greed Index, making it easy to integrate into MCP-compatible clients, including Claude Desktop.
Features
Current Index: Retrieve the latest Fear & Greed Index value and classification.
Historical Data: Fetch historical index values for a specified number of days.
Trend Analysis: Analyze trends over time with statistics like average value and trend direction.
Tool-Only Support: Includes tool versions of all resources for compatibility with tool-only MCP clients.
Prompt Generation: Provides a prompt template for interpreting index values.
Resources
fng://current. Current crypto Fear & Greed Index. Output:
Crypto Fear & Greed Index (as of 2025-03-15 00:00:00 UTC):
Value: 45
Classification: Fearfng://history/{days}. Historical Data of Crypto Fear & Greed Index.Output:
Historical Crypto Fear & Greed Index:
2025-03-15 00:00:00 UTC: 45 (Fear)
2025-03-14 00:00:00 UTC: 48 (Fear)
...Tools
get_current_fng_tool() -> str.
Current Index. Same as fng://current
get_historical_fng_tool(days: int) -> str.
Historical Index Data. Same as fng://history/{days}
analyze_fng_trend(days: int) -> str.
Index trend Analysis. Output:
Fear & Greed Index Analysis (30 days):
Latest Value: 45 (Fear) at 2025-03-15 00:00:00 UTC
Average Value: 47.3
Trend: falling
Data points analyzed: 30Prompts
interpret_fng
Index Data Interpretation.
Output:
Please interpret this Crypto Fear & Greed Index value and explain what it means for cryptocurrency markets (specifically Bitcoin): 45Related MCP server: funding-rates-mcp
Installation
Installing via Smithery
To install Crypto Fear & Greed Index for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @kukapay/crypto-feargreed-mcp --client claudeClone the repository:
git clone https://github.com/kukapay/crypto-feargreed-mcp.git
cd crypto-feargreed-mcpInstall for Claude Desktop
mcp install main.py --name "CryptoFearGreed"Then enable it in your Claude Desktop configuration.
For other clients, add a server entry to your configuration file:
"mcpServers": {
"crypto-feargreed-mcp": {
"command": "uv",
"args": [
"--directory", "/your/path/to/crypto-feargreed-mcp",
"run",
"main.py"
]
}
}Examples
After installation, ask:
"What's the current Crypto Fear & Greed Index?"
"Show me the Crypto Fear & Greed Index trend for the last 30 days."
Claude will automatically call the appropriate tools and provide responses.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Acknowledgments
Built with MCP Python SDK.
Data provided by Alternative.me Fear & Greed Index API.
Available Tools
3 toolsanalyze_fng_trendA
Analyze trends in Crypto Fear & Greed Index over specified days.
Parameters: days (int): Number of days to analyze (must be a positive integer).
Returns: str: A string containing the analysis results, including latest value, average value, trend direction, and number of data points analyzed.
| Name | Required | Description | Default |
|---|---|---|---|
| days | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function and return format, including details like 'latest value, average value, trend direction, and number of data points analyzed.' However, it lacks information on potential limitations (e.g., rate limits, data availability, error conditions) or performance characteristics. The description adds value but isn't comprehensive for behavioral transparency.
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-structured and appropriately sized. It starts with a clear purpose statement, followed by a 'Parameters' section with a concise explanation, and a 'Returns' section detailing the output. Every sentence adds value without redundancy, making it easy for an agent to parse and understand.
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 tool's moderate complexity (1 parameter, no output schema, no annotations), the description is fairly complete. It covers the purpose, parameter semantics, and return format in detail. However, it lacks context on how it differs from sibling tools and doesn't mention potential behavioral aspects like error handling or data sources, leaving some gaps for the agent.
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 significant meaning beyond the input schema, which has 0% description coverage. It explains that 'days' is 'Number of days to analyze (must be a positive integer),' clarifying the parameter's purpose and constraints. This compensates well for the schema's lack of documentation, though it doesn't cover edge cases like maximum allowed days.
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's purpose: 'Analyze trends in Crypto Fear & Greed Index over specified days.' It specifies the verb ('analyze trends'), resource ('Crypto Fear & Greed Index'), and scope ('over specified days'). However, it doesn't explicitly differentiate from sibling tools like 'get_current_fng_tool' or 'get_historical_fng_tool', which likely provide raw data rather than analysis.
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 provides no guidance on when to use this tool versus its siblings ('get_current_fng_tool' and 'get_historical_fng_tool'). It mentions the parameter 'days' but doesn't explain alternative scenarios or prerequisites. Without explicit when/when-not instructions, the agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_current_fng_toolB
Get the current Crypto Fear & Greed Index as a tool.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does without mentioning any behavioral traits such as rate limits, authentication needs, data freshness, or error handling. For a tool with zero annotation coverage, this is a significant gap in transparency.
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 in a single sentence: 'Get the current Crypto Fear & Greed Index as a tool.' It efficiently conveys the core purpose without unnecessary details. However, the phrase 'as a tool' is redundant and could be omitted for better clarity.
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 tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks context on usage guidelines, behavioral traits, or output format. For a tool with no structured data to rely on, the description should provide more completeness to aid the agent effectively.
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 has 0 parameters, and the schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the absence of parameters. A baseline score of 4 is appropriate as the description doesn't need to compensate for any parameter gaps.
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's purpose: 'Get the current Crypto Fear & Greed Index'. It specifies the verb 'Get' and the resource 'Crypto Fear & Greed Index', making the function unambiguous. However, it doesn't explicitly differentiate from its sibling tools (analyze_fng_trend, get_historical_fng_tool), which would require mentioning it retrieves only the current value versus historical data or trend analysis.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools (analyze_fng_trend, get_historical_fng_tool) or specify contexts like needing real-time data versus historical analysis. Without such distinctions, the agent lacks clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_historical_fng_toolC
Get historical Fear & Greed Index for specified number of days as a tool.
Parameters: days (int): Number of days to retrieve (must be a positive integer).
Returns: str: Historical Fear & Greed Index values for the specified period.
| Name | Required | Description | Default |
|---|---|---|---|
| days | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions the tool returns historical values as a string, but lacks details on data format, potential rate limits, error handling, or authentication needs. For a data retrieval tool with zero annotation coverage, this is insufficient.
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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter and return details. It avoids redundancy, though the phrase 'as a tool' is slightly verbose and could be omitted for tighter phrasing.
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 tool's complexity (data retrieval with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return format beyond 'str', missing details like data structure (e.g., JSON, CSV), timestamps, or error cases, which are critical for effective tool use.
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 meaning by specifying that 'days' must be a positive integer and indicates it determines the retrieval period. However, it doesn't clarify constraints like maximum days, date ranges, or default values, leaving gaps in parameter understanding.
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 retrieves historical Fear & Greed Index data for a specified number of days, using specific verbs ('Get', 'retrieve') and identifying the resource. It distinguishes from the sibling 'get_current_fng_tool' by specifying historical data, though it doesn't explicitly differentiate from 'analyze_fng_trend' which might involve analysis rather than retrieval.
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 provides no guidance on when to use this tool versus its siblings. It doesn't mention alternatives like 'get_current_fng_tool' for current data or 'analyze_fng_trend' for trend analysis, nor does it specify prerequisites or exclusions for usage.
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.
3 tool updates
- First observed
analyze_fng_trend - First observed
get_current_fng_tool - First observed
get_historical_fng_tool
TDQS
Scored across 3 tools
The tools have overlapping purposes that could cause confusion. 'analyze_fng_trend' and 'get_historical_fng_tool' both retrieve historical data with a 'days' parameter, making their boundaries unclear. 'get_current_fng_tool' is distinct but the other two appear to serve similar functions with minor differences in output format.
The naming follows a mixed convention. 'analyze_fng_trend' uses snake_case with a verb_noun pattern, while 'get_current_fng_tool' and 'get_historical_fng_tool' also use snake_case but append '_tool' inconsistently. The pattern is readable but lacks full consistency across all tools.
With 3 tools, the count is reasonable for a focused server on Crypto Fear & Greed Index data. It's slightly thin but covers current, historical, and trend analysis, which aligns well with the domain scope without being overly complex.
The tool surface covers basic retrieval and analysis of the index, but there are notable gaps. For example, there's no tool for comparing multiple time periods, setting alerts, or integrating with other crypto data, which could limit agent workflows in a broader crypto analysis context.
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