Tickerdb MCP server
{
"mcpServers": {
"tickerdb": {
"command": "npx",
"args": [
"-y",
"tickerdb-mcp@latest",
"tickerdb-mcp"
],
"env": {
"TICKERDB_KEY": "<tickerdb_key>",
"MCP_PUBLISHER_KEY": "<mcp_publisher_key>"
}
}
}
}{
"mcpServers": {
"tickerdb": {
"command": "npx",
"args": [
"-y",
"tickerdb-mcp@latest",
"tickerdb-mcp"
],
"env": {
"TICKERDB_KEY": "<tickerdb_key>",
"MCP_PUBLISHER_KEY": "<mcp_publisher_key>"
}
}
}
}{
"mcpServers": {
"tickerdb": {
"command": "npx",
"args": [
"-y",
"tickerdb-mcp@latest",
"tickerdb-mcp"
],
"env": {
"TICKERDB_KEY": "<tickerdb_key>",
"MCP_PUBLISHER_KEY": "<mcp_publisher_key>"
}
}
}
}{
"servers": {
"tickerdb": {
"command": "npx",
"args": [
"-y",
"tickerdb-mcp@latest",
"tickerdb-mcp"
],
"env": {
"TICKERDB_KEY": "${input:tickerdb_key}",
"MCP_PUBLISHER_KEY": "${input:mcp_publisher_key}"
}
}
},
"inputs": [
{
"id": "tickerdb_key",
"type": "promptString",
"description": "Tickerdb key",
"password": true
},
{
"id": "mcp_publisher_key",
"type": "promptString",
"description": "Mcp publisher key",
"password": true
}
]
}{
"mcpServers": {
"tickerdb": {
"command": "npx",
"args": [
"-y",
"tickerdb-mcp@latest",
"tickerdb-mcp"
],
"env": {
"TICKERDB_KEY": "<tickerdb_key>",
"MCP_PUBLISHER_KEY": "<mcp_publisher_key>"
}
}
}
}file .mcp.json (in your project root)file claude_desktop_config.jsonfile ~/.cursor/mcp.jsonfile .vscode/mcp.jsonfile ~/.codeium/windsurf/mcp_config.jsoninstall npx -y tickerdb-mcpversion 1.8.6
What it does
TickerDB provides pre-computed market data for AI agents, including 182 technical and fundamental indicators across 10,000+ US stocks, ETFs, and crypto pairs. It exposes categorical states (like "oversold" or "strong_uptrend"), state transition history, and predictive distributions, allowing agents to reason about market conditions without computing indicators from raw data. Intended for developers building AI agents that need to analyze stocks or perform market screening.
- Screen for stocks matching multiple conditions (e.g., oversold large-cap stocks near support) using categorical filters instead of raw numbers.
- Analyze what typically happens after a specific market state (e.g., historical distribution of AAPL price action following oversold entries over 7 years).
- Track a watchlist and identify only what changed (state transitions) rather than pulling full summaries for every ticker.
Tools this server exposes
| Tool | Does |
|---|---|
| get_summary | Returns technical and fundamental snapshot for a ticker, including state transition history and predictive distributions for a given market state. |
| get_ohlcv | Returns daily or weekly end-of-day candles for use in returns calculations, charting, or backtesting. |
| get_search | Screens assets by categorical state or ranks them by fields such as market cap or PE ratio. |
| get_schema | Discovers all 182 available fields and their valid categorical band values. |
| get_watchlist | Returns full analytical summary for every ticker on a saved watchlist. |
| get_watchlist_changes | Returns only field-level state transitions (band entries, exits, and shifts) on a watchlist since the last check. |
| add_to_watchlist | Adds tickers to a saved watchlist. |
| remove_from_watchlist | Removes tickers from a saved watchlist. |
| get_account | Returns account details, plan tier, and API usage information. |
Before you enable it
An MCP server runs with whatever access you give it. Start with a development account rather than production, and check which tools the server exposes before you let an agent call them unattended.