Skip to contentMode VC AI Chart Lab: 38 Empirical AI & Venture Charts MCP | MCPpediaMMode VC AI Chart Lab: 38 Empirical AI & Venture Charts MCP Server
Query empirical frontier LLM release velocity, inference token deflation, and enterprise AI spend.
52FairInstall
~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"harrybuild-modevc-ai-charts-mcp": {
"url": "https://modevc.com/api/mcp/llm-economics"
}
}
}
Environment
This server does not declare environment variables.
Related servers
CCodebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
HLocal-first agentic RAG with citations - hybrid search, reranking, multimodal document retrieval
Tools show up when the registry metadata or the repository README lists them. GitHub enrichment fills this in when a token is configured.
About
Query empirical frontier LLM release velocity, inference token deflation, and enterprise AI spend.
FAQ
- What is Mode VC AI Chart Lab: 38 Empirical AI & Venture Charts?
- Query empirical frontier LLM release velocity, inference token deflation, and enterprise AI spend.
- How do I install Mode VC AI Chart Lab: 38 Empirical AI & Venture Charts?
- Pick a client above and copy the generated config. Cursor and VS Code also have a deep link when the server can run locally or remotely.
- Is Mode VC AI Chart Lab: 38 Empirical AI & Venture Charts official?
- No. Registry-listed is not the same as vendor-official. Read the methodology for the difference.
- How is the trust score calculated?
- This listing scores 52 (Fair). The formula is published on the methodology page.
Reviews
0 published · no average
Sign in to review this server.
OInvestment runtime for AI agents — LLM investment committee, portfolio ledger, decision accounting
MLocal-first, cloud-friendly memory — 100+ tools, 99.2% LongMemEval-S retrieval@8, hybrid search.

Shared, verifiable memory for machines and AI. Encode where data lives; decode with any AI.
CTerminal output, project snapshots and semantic diffs as LLM-ready context