Kinetic Gain MCP

mcp-kinetic-gain

Unified MCP server for the eleven Kinetic Gain Protocol Suite specs plus a DefenseTech 6-pack. 71 tools, one Claude Desktop config, no API key.

75 tools GitHub npm

No known CVEs

AGPL-3.0 license

Actively maintained

Last commit 9d ago

Works with most clients

Transport: stdio, sse, http

75 tools · ~3.6k tok

Grade C · 1.8% of 200K ctx

MCPpedia last refreshed this data 17h ago

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Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "kinetic-gain": {
      "args": [
        "-y",
        "mcp-kinetic-gain"
      ],
      "command": "npx"
    }
  }
}

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What Kinetic Gain MCP does

MCP server and CLI for all eleven Kinetic Gain Protocol Suite specs plus DefenseTech 6-pack tooling. One Claude Desktop config, no API key, stdio transport. 71 tools (47 spec + 16 implementation-preview + 8 DefenseTech) covering AEO Protocol, Prompt Provenance, Agent Cards, AI Evidence Format, MCP Tool Cards, AI Tutor Cards, Student AI Disclosure, Classroom AI AUP, Clinical AI Disclosure, AI Incident Card, and AI Procurement Decision Card, plus ed25519 hash attestation. AGPL-3.0.

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

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Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

79/100across 5 weighted dimensions

How we score →

0255075100

−21

Security

Maintenance

Efficiency

Documentation

Compatibility

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Security

OSV.dev

No known CVEs.

Checked mcp-kinetic-gain against OSV.dev.

Inventory

Tools (75)

Click any tool to inspect its schema.

~3.6k tokens total

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Frequently Asked Questions

Is Kinetic Gain MCP safe to use?: Kinetic Gain MCP has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under AGPL-3.0.
How do I install Kinetic Gain MCP?: Kinetic Gain MCP supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can Kinetic Gain MCP do?: Kinetic Gain MCP provides 75 tools: aeo_fetch, aeo_inspect, aeo_get_claim, aeo_well_known_url, prompt_provenance_validate and 70 more. See the full tools list on the server page for descriptions and parameters.
What AI clients work with Kinetic Gain MCP?: Kinetic Gain MCP is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is Kinetic Gain MCP actively maintained?: Kinetic Gain MCP is actively maintained — last commit was 9 days ago.

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mcp-kinetic-gain

One MCP server, all twelve Kinetic Gain Protocol Suite specs + the v0.1.0 implementation tooling + the DefenseTech 6-pack. Drop into Claude Desktop, Cursor, or any MCP-compatible client with a single config entry. The agent gains 75 tools (47 spec + 16 implementation-preview + 8 DefenseTech + 4 AI Claims Decision Card, v0.9.0): AEO Protocol, Prompt Provenance, Agent Cards, AI Evidence Format, MCP Tool Cards, AI Tutor Cards, Student AI Disclosure, Classroom AI AUP, Clinical AI Disclosure, AI Incident Card, AI Procurement Decision Card, AI Claims Decision Card - plus hash attestation (ed25519), audit-stream event composition + chain verification (offline AND live against a running audit-stream-py via AUDIT_STREAM_URL), cross-spec drift detection, Decision Intelligence preview, and the DefenseTech vault resolver + invariant checkers. New in v0.9.0: the AI Claims Decision Card (InsurTech, claims_card_version) - claims_card_validate, claims_card_inspect, claims_card_sign, claims_card_chain.

This is the unified read-side companion to kinetic-gain-visualizer: the visualizer renders any of the 12 specs for humans, this server exposes them as callable tools for agents.

Tools

75 tools

aeo_fetch - Fetch the full AEO Protocol declaration at an origin's
aeo_inspect - Return a structured summary of an AEO declaration: entity
aeo_get_claim - Extract a single AEO claim by ID
aeo_well_known_url - Compute the canonical AEO well-known URL for an origin
prompt_provenance_validate - Validate a Prompt Provenance JSON document against the v0.1
prompt_provenance_inspect - Structured summary of a Prompt Provenance document: prompt
prompt_provenance_eval_result - Extract a single evaluation suite's result from a Prompt
agent_card_well_known_url - Compute the canonical Agent Card well-known URL for a given
agent_card_inspect - Structured summary of an Agent Card document
agent_card_tool_disclosure - Return the list of tools an agent declares, with side-effect
agent_card_validate - Validate an Agent Card JSON document against the v0.1 schema.
ai_evidence_validate - Validate an AI Evidence object against the v0.1 schema.
ai_evidence_inspect - Structured summary of an AI Evidence object: claim text
ai_evidence_verify_hash - Compute SHA-256 over the canonical UTF-8 form of
tool_card_well_known_url - Compute the canonical MCP Tool Card well-known URL
tool_card_inspect - Structured summary of an MCP Tool Card: tool identity, safety
tool_card_tested_with - Return the tested-LLM entries for a tool, optionally filtered
tool_card_validate - Validate an MCP Tool Card JSON document against the v0.1
tutor_card_well_known_url - Compute the canonical AI Tutor Card well-known URL
tutor_card_fetch - Fetch a Tutor Card from a URL
tutor_card_validate - Validate an AI Tutor Card JSON document against the v0.1
tutor_card_inspect - Structured summary of a Tutor Card: tutor identity, audience
tutor_card_subject_check - Classify a topic against the tutor's subject scope
tutor_card_coppa_check - Enforce the spec's COPPA conditional rule: if
disclosure_validate - Validate a Student AI Disclosure JSON document against the
disclosure_inspect - Structured summary of a Student AI Disclosure: assignment
disclosure_verify_artifact_hash - Recompute SHA-256 over a candidate artifact and compare to
disclosure_verify_prompt_hash - Verify a single prompt hash in a hashed-mode disclosure
disclosure_aup_check - Surface the disclosure's policy posture: whether an aup_uri
aup_well_known_url - Compute the canonical Classroom AI AUP well-known URL
aup_fetch - Fetch a Classroom AI AUP from a URL

... View full README on GitHub

Frequently Asked Questions

Is Kinetic Gain MCP safe to use?

Kinetic Gain MCP has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under AGPL-3.0.

How do I install Kinetic Gain MCP?

Kinetic Gain MCP supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What can Kinetic Gain MCP do?

Kinetic Gain MCP provides 75 tools: aeo_fetch, aeo_inspect, aeo_get_claim, aeo_well_known_url, prompt_provenance_validate and 70 more. See the full tools list on the server page for descriptions and parameters.

What AI clients work with Kinetic Gain MCP?

Kinetic Gain MCP is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

Is Kinetic Gain MCP actively maintained?

Kinetic Gain MCP is actively maintained — last commit was 9 days ago.

mcp-kinetic-gain

This is the unified read-side companion to kinetic-gain-visualizer: the visualizer renders any of the 12 specs for humans, this server exposes them as callable tools for agents.

Tools

75 tools

aeo_fetch - Fetch the full AEO Protocol declaration at an origin's
aeo_inspect - Return a structured summary of an AEO declaration: entity
aeo_get_claim - Extract a single AEO claim by ID
aeo_well_known_url - Compute the canonical AEO well-known URL for an origin
prompt_provenance_validate - Validate a Prompt Provenance JSON document against the v0.1
prompt_provenance_inspect - Structured summary of a Prompt Provenance document: prompt
prompt_provenance_eval_result - Extract a single evaluation suite's result from a Prompt
agent_card_well_known_url - Compute the canonical Agent Card well-known URL for a given
agent_card_inspect - Structured summary of an Agent Card document
agent_card_tool_disclosure - Return the list of tools an agent declares, with side-effect
agent_card_validate - Validate an Agent Card JSON document against the v0.1 schema.
ai_evidence_validate - Validate an AI Evidence object against the v0.1 schema.
ai_evidence_inspect - Structured summary of an AI Evidence object: claim text
ai_evidence_verify_hash - Compute SHA-256 over the canonical UTF-8 form of
tool_card_well_known_url - Compute the canonical MCP Tool Card well-known URL
tool_card_inspect - Structured summary of an MCP Tool Card: tool identity, safety
tool_card_tested_with - Return the tested-LLM entries for a tool, optionally filtered
tool_card_validate - Validate an MCP Tool Card JSON document against the v0.1
tutor_card_well_known_url - Compute the canonical AI Tutor Card well-known URL
tutor_card_fetch - Fetch a Tutor Card from a URL
tutor_card_validate - Validate an AI Tutor Card JSON document against the v0.1
tutor_card_inspect - Structured summary of a Tutor Card: tutor identity, audience
tutor_card_subject_check - Classify a topic against the tutor's subject scope
tutor_card_coppa_check - Enforce the spec's COPPA conditional rule: if
disclosure_validate - Validate a Student AI Disclosure JSON document against the
disclosure_inspect - Structured summary of a Student AI Disclosure: assignment
disclosure_verify_artifact_hash - Recompute SHA-256 over a candidate artifact and compare to
disclosure_verify_prompt_hash - Verify a single prompt hash in a hashed-mode disclosure
disclosure_aup_check - Surface the disclosure's policy posture: whether an aup_uri
aup_well_known_url - Compute the canonical Classroom AI AUP well-known URL
aup_fetch - Fetch a Classroom AI AUP from a URL

... View full README on GitHub