Catalyst Edge Research runs on your own machine — the client starts it, so there is no endpoint to ping. 271 installs a week from pypi. Last commit 26 Aug 2026.
Source-linked market intelligence for AI agents researching public-company tickers.
Today is the operative word: we check Catalyst Edge Research every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add catalyst-edge-mcp -- uvx catalyst-edge-mcp
{
"mcpServers": {
"catalyst-edge-mcp": {
"args": [
"catalyst-edge-mcp"
],
"command": "uvx"
}
}
}
[mcp_servers.catalyst-edge-mcp]
command = "uvx"
args = ["catalyst-edge-mcp"]
{
"mcpServers": {
"catalyst-edge-mcp": {
"args": [
"catalyst-edge-mcp"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"catalyst-edge-mcp": {
"args": [
"catalyst-edge-mcp"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
CATALYST_EDGE_SEC_USER_AGENT (Required SEC-compliant identity in Company [email protected] form for live evidence collection.), CATALYST_EDGE_EVIDENCE_STORE (Optional local SQLite evidence-store path.), CATALYST_EDGE_GDELT (Rights-cleared attributed discovery metadata defaults to enabled; set to disabled to opt out.), CATALYST_EDGE_BLUESKY (Optional explicit opt-in: set to enabled for forward-only partial public attention; defaults to disabled.).
The author declared them in the registry entry; get the values from the project itself.
Market research and competitive intelligence for startup ideas - every finding source-linked.
US public-records intelligence for AI agents — companies, SEC, courts, spending, licenses.
x402-paid analytics, market intelligence, research, and LLM inference for AI agents.
Pay-per-call trading intelligence for AI agents: live market regime, trading signals, composite conv
Public source-linked memories for AI agents: search, read, cite, reply, and share findings.
Equity trend, relative-strength, expected-return, market-context, and research resources for agents.
The Google for AI agents — company intel, competitor tracking, market research via MCP. JSON output
Research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.
Answers built from our own checks of this server.