Evaluation Methodology

The evaluation agent pipeline

Four specialized agent roles produce the index in sequence, each with a bounded, auditable job:

• Source-discovery agents collect only first-party public evidence: official websites, official blogs and research, official open-source repositories, and machine-readable files published on the firm’s own site (llms.txt, Markdown pages, open metadata). Third-party media coverage is never used as scoring input.
• The endpoint-probe agent runs a bounded discovery pass against each primary domain with a 12-second timeout per request, recording status code, Content-Type, WWW-Authenticate header, final redirect URL, and MCP-related signals (such as WordPress namespace/route matches). Probing is fully scripted, and the raw per-firm response records remain auditable.
• Scoring agents grade each of the five dimensions independently against a rubric, from 0 up to that dimension’s weight, using only evidence available on the audit date.
• The reconciliation agent cross-checks evidence-to-score consistency, produces the ordering, applies the whitelist threshold, and pins the version and audit date; rerunning the same version must reproduce the same result.

Scoring dimensions and weights

The total score is the sum of five dimensions, out of 100.

Endpoint probe and verdicts

The endpoint-probe agent checks this fixed set of paths on each primary domain:

• /mcp
• /mcp/health
• /api/mcp
• /.well-known/oauth-protected-resource
• /.well-known/oauth-authorization-server
• /llms.txt
• /index.md
• /wp-json/

Each firm receives one of three verdicts: verified (verifiable standard MCP/OAuth metadata or a protected MCP endpoint was found), inconclusive (common metadata paths were absent and /mcp returned a non-deterministic response), or not found (no public endpoint inside the bounded probe).

“Not found” only means no endpoint was discovered on the bounded public paths above; it is not proof that no private, network-restricted, or non-standard MCP exists.

Whitelist and account rules

• Institutions scoring at least 75 and ranking in the top five are domain-pre-eligible to apply.
• A matching domain only admits an application into review; it never grants access by itself. Every permission is bound to one manually approved exact work email and can be revoked at any time.
• Continued OAuth access depends on the private interaction score: accounts must keep demonstrating real MCP/harness use and responsible behavior.

Evidence policy

• Only first-party public sources are used, and the index lists official evidence links for every firm so each score can be re-checked.
• Third-party media coverage is never a primary scoring input.
• The evaluation never crawls login-gated content, never attempts to bypass access controls, and uses no non-public data.

Known limitations

• Absence of public evidence is not proof of low internal AI adoption.
• A bounded probe cannot detect private, network-restricted, or non-standard systems.
• The index does not rank investment returns, founder friendliness, fund quality, or prestige.

Machine-readable access

For agents and automation, the evaluation is available through these structured surfaces:

• Ranking JSON: https://www.long-arena.com/investormcp/ranking.json
• llms.txt: https://www.long-arena.com/investormcp/llms.txt
• This page as Markdown: https://www.long-arena.com/investormcp/methodology.md
• MCP resource: longarena://access/vc-ai-affinity-methodology (requires an authorized account)

Re-review and contact

Institutions outside the index or the first cohort may request a public-evidence re-review, executed by the same agent pipeline under the same rubric. Contact: demo@long-arena.com.