KanseiLink MCP Server

Reduce your AI agent's token waste with collective intelligence.

Your agent burns tokens on three things: searching for SaaS docs it could look up locally, retrying errors other agents already solved, and re-reading context it already processed. KanseiLink tackles the first two — and measures all three so you know exactly where your tokens go.

Measured savings: 89–97% on SaaS integration research (avg ~16,800 tokens without → ~950 with KanseiLink, across 7 services).

How It Works

Install MCP → agent wastes fewer tokens (lookup + collective intelligence)
                    ↓
            usage data stays local (opt-in: anonymous scalars only)
                    ↓
            collective intelligence grows → everyone's agent gets smarter

1. Measure — auto-installed hooks track every session: total tokens, cache split, error loops, stuck time. Nothing leaves your machine.
2. Reduce — SaaS lookup eliminates trial-and-error on API integrations. Error-resolution intelligence (coming soon) prevents repeat failures across the community.
3. Compare — opt-in monthly "Wrapped" report shows where your tokens went and how you rank among measured users.

If KanseiLink saves your agent tokens, give it a star ⭐ — 700+ developers install it from npm every month, and stars are how the next one finds it.

Quick Start

npx @kansei-link/mcp-server

Works with Claude Code, Cursor, Cline, Zed, Windsurf — any MCP client.

Add to your config (claude_desktop_config.json, .cursor/mcp.json, etc.):

{
  "mcpServers": {
    "kansei-link": {
      "command": "npx",
      "args": ["-y", "@kansei-link/mcp-server"]
    }
  }
}

Or with Claude Code CLI:

claude mcp add -s user kansei-link -- npx -y @kansei-link/mcp-server

Wrapped: Your Monthly Agent Fuel-Efficiency Report

KanseiLink measures — locally, on your machine — how many tokens your agent sessions consume and how much of that KanseiLink saved you, then renders a monthly "Wrapped" share card.

1. Install the measurement hooks (one command, idempotent, backs up your settings first):

npx -y -p @kansei-link/mcp-server kansei-link-install-hooks

This adds a Stop/SessionEnd hook that parses each session transcript and writes token totals + KanseiLink call stats to ~/.kansei-link/usage/. Nothing is uploaded.

2. See your report any time:

npx -y -p @kansei-link/mcp-server kansei-link-wrapped            # current month (JA)
npx -y -p @kansei-link/mcp-server kansei-link-wrapped --lang en  # English
npx -y -p @kansei-link/mcp-server kansei-link-wrapped --share    # opt-in: get your rank

The report separates measured numbers (your total tokens, KanseiLink call counts and response sizes — parsed from your own transcripts) from estimated ones (the avoided web-research cost, based on the 2026-04-16 freee/kintone/smarthr benchmark) — labels shown on every surface.

It also shows where your agent got stuck: failed tool calls, retry chains (2+ consecutive failures of the same tool), the tokens burned while stuck, and your worst-failing tools.

--share submits only scalar monthly aggregates (anonymous id + token counts, never content) and returns how you rank among measured users ("top X% saver"). Below 20 measured users for the month, you get the cohort size instead of a rank.

Disable measurement anytime: export KANSEI_USAGE_HOOK=off, or kansei-link-install-hooks --remove.

SaaS Integration Intelligence

The core reason agents waste tokens on SaaS APIs: they search docs, guess auth flows, and recover from errors — every single time. KanseiLink ships a local SQLite DB so your agent gets the answer on the first try.

All data ships inside the npm package as a local SQLite DB. Zero API calls needed. No server dependency, no signup.

Without vs. With KanseiLink

Claude Code: install the skill (auto-invocation)

Installing the MCP alone doesn't teach Claude Code when to call KanseiLink. The bundled skill fixes that:

npx -y -p @kansei-link/mcp-server kansei-link-install-skill

This copies a SKILL.md to ~/.claude/skills/kansei-link/. Claude Code auto-discovers it and fires the skill on phrases like "connect to Stripe", "Slack MCPある？", "send invoice via freee" — no need to say "use KanseiLink".

Optional: PostToolUse hook

Auto-capture success/failure after every MCP call (agents tend to forget reporting).

Consent (v1.2, BREAKING). Installing the hook alone no longer transmits anything. All central transmission is governed by one consent gate (~/.kansei-link/consent.json), with this priority: DO_NOT_TRACK=1 / explicit OFF → explicit ON (KANSEI_REPORT_HOOK=on) → Live Updates consent (npx -y -p @kansei-link/mcp-server kansei-link-live-updates --enable) → default OFF (Local Mode, zero transmission). Existing hook users are OFF until they re-consent. Manage: kansei-link-live-updates --status|--enable|--disable, kansei-link-privacy --status|--reset-id.

What this hook sends when enabled (and what it never sends). A small pseudonymous event to KanseiLink's hosted endpoint after each MCP tool call. The payload is a fixed 7-field set, frozen by a snapshot test (scripts/smoke-hook-payload.mjs):

• sent: service slug (or MCP server name), success/failure, tool name, error category (e.g. auth_error), a fixed context string
• never sent: prompts, tool inputs/outputs, page/customer/record names, API keys, file paths, free text of any kind. No account or machine identifier is attached.

Installing the hook does NOT opt you in — transmission requires the consent gate above (Live Updates consent, or an explicit KANSEI_REPORT_HOOK=on). Disable anytime: kansei-link-live-updates --disable or export KANSEI_REPORT_HOOK=off.

Add to ~/.claude/settings.json:

{
  "hooks": {
    "PostToolUse": [{
      "matcher": "mcp__.*",
      "hooks": [{ "type": "command", "command": "npx -y -p @kansei-link/mcp-server kansei-link-report-hook" }]
    }]
  }
}

Disable anytime: export KANSEI_REPORT_HOOK=off

Tools (5)

v1.0 consolidates the tool surface from 25 individual tools into 5 unified tools with mode auto-detection.

Standard Flow (3 tools — all you need)

search_services --> lookup --> (execute your API call) --> report

Admin Tools (2 additional)

Lookup Modes

Report Modes

Example Workflows

Find and integrate a service:

search_services({ intent: "send invoice to clients", compact: true })
--> lookup({ service_id: "freee" })        // tips: auth, pitfalls, workarounds
--> lookup({ service_id: "freee", detail: true })  // full connection guide
--> (execute your API call)
--> report({ service_id: "freee", success: true, task_type: "create_invoice" })

Multi-service workflow:

lookup({ goal: "create invoice and notify via slack", services: ["freee", "slack"] })
--> Step-by-step recipe with coverage scoring

Share your honest opinion:

report({
  service_id: "stripe",
  question_id: "biggest_frustration",
  response_text: "Webhook signature verification docs are unclear for non-Node runtimes"
})

Categories (23)

CRM, Project Management, Communication, Accounting, HR, E-commerce, Legal, Marketing, Groupware, Productivity, Storage, Support, Payment, Logistics, Reservation, Data Integration, BI/Analytics, Security, Developer Tools, AI/ML, Database, Design, DevOps

Architecture

Agent <-> KanseiLink MCP Server <-> SQLite (local, zero-config)
              |
              +-- search_services  -> FTS5 + trigram (CJK) + LIKE + category detection
              +-- lookup           -> tips / detail / insights / recipe / combinations /
              |                       history / feedback / voices (auto-detected)
              +-- report           -> outcome / feedback / event / voice (auto-detected)
              +-- inspect          -> queue / submit / propose / review / snapshot / evaluate
              +-- analyze          -> token_savings / cost / aeo_report / aeo_article

For SaaS Companies

KanseiLink doubles as an Agent Readiness Index (ARI) evaluation platform. Real agents using real APIs generate objective telemetry — success rates, latency, error patterns, and resolution paths — that no survey or benchmark can replicate.

What we can show you:

• Agent success rate for your API over time
• Error patterns and how agents work around them
• Agent Voice: why agents choose (or avoid) your service
• Category ranking vs competitors
• Impact of API changes (before/after analysis)

This data comes from the same MCP that saves individual developers tokens — the collective intelligence that helps agents is the same signal that evaluates services.

See kansei-link.com or reach out.

Privacy & Data Handling

KanseiLink is privacy-preserving by default:

• Local-first: the full service DB ships inside the npm package. No API calls needed.
• Measurement stays local: the usage hook writes to ~/.kansei-link/usage/ on your machine. Nothing is uploaded unless you opt in with --share, which sends only scalar aggregates (token counts), never content.
• PII auto-masking: every report call scrubs emails, phone numbers, IP addresses, and Japanese names before storage.
• Agent identity anonymized: only the agent type (claude / gpt / gemini) is retained — never the user ID.
• No telemetry by default: the local stdio server does not phone home.

See SECURITY.md for full details.

Troubleshooting

Contributing

git clone https://github.com/kansei-link/kansei-mcp-server.git
cd kansei-mcp-server
npm install
npm run build
npm start       # start stdio server

PRs welcome. If you find a service that's missing or has wrong info, the fastest path is:

report({ subject: "Fix: ServiceX auth is OAuth2 not API key", body: "..." })

Links

• npm
• Website
• MCP Registry: io.github.kansei-link/kansei-mcp-server
• Glama

License

MIT — Synapse Arrows PTE. LTD.