Analyzes Bitcoin market regimes, historical matches, probabilities, macro signals, and cycle indicators through MCP tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Signallord MCP Server.
signallord_get_regimeCurrent regime, historical matches, outcome probabilities
signallord_get_regime_historyRegime evolution over time from daily snapshots
signallord_get_composite_scoreComposite 0-100 score with regime label
signallord_get_gauge_breakdownIndividual gauge scores (4 free, 8 premium)
signallord_get_gauge_historyHistorical scores for trend analysis
signallord_get_odin_analysisAI market analysis (basic free, enriched premium)
KK6BZB/signallord-mcp-server MCP server gives AI agents access to Signal Lordβs Bitcoin regime and market-analysis features. Its tools identify the current market regime, compare present conditions with historical periods, and return probabilities for possible outcomes. The service also exposes composite scores, gauge histories, macro indicators, institutional data, derivatives metrics, exchange flows, liquidations, and several Bitcoin cycle indicators.
The toolset includes 26 operations grouped around regime detection, gauges, Odin AI, market data, signals, cycle indicators, probability playbooks, and data health. Examples include signallord_get_regime, signallord_get_composite_score, signallord_get_macro_indicators, signallord_ask_odin, and signallord_get_data_health. Some tools or fields return limited information on the free tier, while premium and pro tiers provide broader data access.
The server acts as a stateless MCP protocol adapter. An AI client sends MCP tool requests to the local process, which makes HTTP requests to the configured Signal Lord backend. Authentication is passed through the X-SIGNALLORD-API-KEY header. Regime detection, historical matching, rate limiting, data collection, and Odin AI processing are handled by the backend rather than locally.
The default local transport is streamable HTTP, with the server listening on port 8100. Clients can connect through the local MCP endpoint at /mcp, or configure a local command in Claude Desktop. The README also identifies Claude and Cursor as example AI agents in the architecture.
To run KK6BZB/signallord-mcp-server MCP server, install the published package globally with npm, and ensure Python 3.10 or newer and pip are available on the system. The package installs its dependencies automatically. The executable is signallord-mcp.
Create an account at Signal Lord and generate an API key. The key is shown only once and should be assigned to SIGNALLORD_API_KEY. SIGNALLORD_API_BASE_URL selects the backend URL; the documented production value is https://signallord.onrender.com, while the server default is http://localhost:8000. MCP_SERVER_PORT controls the local listening port and defaults to 8100.
After starting the process, connect an MCP client to http://localhost:8100/mcp, or use a client configuration that launches signallord-mcp with the required environment variables.
KK6BZB/signallord-mcp-server MCP server requires a Signal Lord API key and access to the configured backend. Availability and detail depend on the account tier: the documented free tier includes 10 requests per minute and 500 per day, while premium and pro tiers have higher limits and additional data.
The data-health tool can identify signals that are stale because of upstream data problems. This matters when an agent uses current gauges, market metrics, or derived indicators. The server provides analysis and historical probabilities, not a guarantee of future Bitcoin price movements. The project is licensed under MIT.
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