Best Free Tools for VC Research

The genuinely free VC research stack in 2026 is three layers, not one product. A discovery signal (what should I look at this week?), a verification database (what is this company's history?), and a workflow surface (where does the research live?). Every layer has a free option good enough for solo use, and the paid upgrades only become necessary at fund scale.

Layer 1, discovery: free signal feeds. This site's core offer sits here: weekly commit-velocity rankings across 350+ venture-relevant startups, sector sweeps, and single-startup signals, all public, with the MCP server (npx -y @gitdealflow/mcp-signal) putting the same six tools inside Claude Desktop or Cursor at no cost. Complement it with GitHub's own trending views for raw technical signal. None of this requires an account.

Layer 2, verification: free database tiers. Crunchbase's free tier gives limited company views and alerts, enough to check last round and investors for a shortlist. Dealroom's free views cover European depth. OpenVC keeps most founder-facing workflow free. PitchBook ($20k+/yr) and CB Insights ($35k+/yr) have no free tier and are not missing from a solo stack; they are institutional verification tools.

Layer 3, workflow: sheets, Airtable, and agents. A spreadsheet is still the honest CRM at zero volume. The 2026 addition is agent workflows: with the MCP server installed, "pull trending fintech startups and draft a memo skeleton" is a single sentence in Claude or Cursor, and the JSON and CSV endpoints script the same pull into any notebook or BI tool. Research time collapses not because any single tool is smarter but because the copy-paste layer between data and document disappears.

The weekly ritual that makes it work. Monday: trending feed, triage 15 minutes, shortlist 3-5 names. For each: free database check, one signal pull, log in the sheet with a next-touch date. Friday: recheck the watchlist for acceleration. Total tool cost: zero. When deal flow volume or LP reporting outgrows this, the upgrade path on the comparison pages states every price plainly, including this site's own €49/month dashboard tier.

The weekly signal report is the anchor of the discovery layer. A free email, no credit card required, surfaces five breakout startups every Monday, giving a solo angel a fixed cadence to triage rather than an open-ended crawl of the whole market. Paired with the same site's public dataset, which tracks 350+ startups across 15 sectors and updates weekly, the Monday email becomes a starting point that the underlying tools can then be pointed at for depth.

The raw data is free to read and script. The public endpoints, signals.json, signals.csv, and dataset.jsonl, are free for personal and editorial use with attribution, so the same numbers behind the dashboard can be pulled into a notebook, a sheet, or a custom script without a paid account. The MCP server exposes the equivalent six read-only tools, trending startups, sector search, single-startup signal, dataset summary, scout receipts, and methodology, with no API key and no rate limit beyond GitHub's own.

The catch is depth, not access. The free tier is structurally permanent rather than a trial, and new paid features land in a separate paid tier rather than being extracted from the free layer. The trade is depth: the paid tier adds full-universe filtering and a set of Scout Game predictions per month, while the free tier keeps the weekly digest and the read-only tools. Nothing a free user already has gets taken away when a paid feature ships.

Honourable mentions round out the stack. SEC EDGAR covers free public filings for public-private overlap research, Hacker News and GitHub Trending add free attention-velocity context, and OpenVC keeps a free founder-pitch directory for inbound. Each is marginal on its own but useful alongside the core three-layer stack, and the right posture is to start free, upgrade only when a specific bottleneck appears, and never pay for a tool that solves a hypothetical future problem.