Tokmeter — AI Agent Usage & Cost
NPM · @SRIINNU/TOKMETER-MCP · SCANNED SEP 24
Tokens and cost for Claude Code, Codex and 14 more AI coding agents, from local session files.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 46 of 146 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to sriinnu/tokmeter). View diagnostics → Pass
- Clear OSI-approved license (AGPL-3.0-only).Pass
- Actively maintained (last published 0 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability76
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 2875 tokens (~119/item across 24 items; 24 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "tokmeter_cleanup_execute" implies "execute" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 24 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
How do I install the Tokmeter — AI Agent Usage & Cost MCP server?
Tokmeter — AI Agent Usage & Cost runs locally as an npm package, launched with npx -y @sriinnu/tokmeter-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · @sriinnu/tokmeter-mcp
claude mcp add sriinnu-tokmeter -- npx -y @sriinnu/tokmeter-mcp
{
"mcpServers": {
"sriinnu-tokmeter": {
"command": "npx",
"args": [
"-y",
"@sriinnu/tokmeter-mcp"
]
}
}
} {
"servers": {
"sriinnu-tokmeter": {
"command": "npx",
"args": [
"-y",
"@sriinnu/tokmeter-mcp"
]
}
}
} codex mcp add sriinnu-tokmeter -- npx -y @sriinnu/tokmeter-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"sriinnu-tokmeter": {
"type": "local",
"command": [
"npx",
"-y",
"@sriinnu/tokmeter-mcp"
],
"enabled": true
}
}
} openclaw mcp add sriinnu-tokmeter --command npx --arg -y --arg @sriinnu/tokmeter-mcp
mcp_servers:
sriinnu-tokmeter:
command: "npx"
args: ["-y", "@sriinnu/tokmeter-mcp"] {
"McpServers": {
"sriinnu-tokmeter": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"@sriinnu/tokmeter-mcp"
]
}
}
} assistant mcp add sriinnu-tokmeter -t stdio -c npx -a -y @sriinnu/tokmeter-mcp
{
"mcpServers": {
"sriinnu-tokmeter": {
"command": "npx",
"args": [
"-y",
"@sriinnu/tokmeter-mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 24 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 23 Sept 26 64
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 24 Sept 2026 · Analysed npm/@sriinnu/tokmeter-mcp@1.13.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | npm |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | sriinnu/tokmeter |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/sriinnu/tokmeter/.github/workflows/publish.yml@refs/tags/v1.13.0 |
| Rekor log index | 2924584952 |
| Predicate type | https://slsa.dev/provenance/v1 |
| Subject digest | sha512:9cafcfbe6d379f94a5944b19cd5462f989bf0ac2624b1e19686bf059c79f6a0d795b3b5d24504273d1a8d83a0600e2409d533107cd1d7698b8f8c6d96 |
Background: How many MCP packages publish verified provenance →
Dependencies 146 packages
| Packages resolved | 146 |
|---|---|
| Stale | 46 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
tokmeter_anomaly ~131
Detect unusual spending patterns and anomalies in token usage. Identifies days or sessions with cost spikes, sudden model switches, abnormally large requests, and deviation from historical averages. Use this to catch runaway costs or unexpected usage.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
| sensitivity | string | – | Anomaly detection sensitivity (default: medium) |
No output schema declared.
No examples provided.
tokmeter_backups ~25
List available cleanup backups with metadata (date, size, providers, projects).
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
tokmeter_budget ~126
Monitor spending against a budget with visual progress bars and alerts. Set a daily, weekly, or monthly budget and see how close you are to the limit. Shows projected overshoot/undershoot. Use this to stay within spending targets.
| Name | Type | Req | Description |
|---|---|---|---|
| daily_budget | number | – | Daily budget in USD |
| monthly_budget | number | – | Monthly budget in USD |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| weekly_budget | number | – | Weekly budget in USD |
No output schema declared.
No examples provided.
tokmeter_budget_alert ~90
Proactive budget monitoring with configurable daily/weekly/monthly thresholds. Shows current spend, percentage of budget used, projected end-of-period spend, and hours remaining until budget is exceeded. Gives green/yellow/red status indicators.
| Name | Type | Req | Description |
|---|---|---|---|
| daily_budget | number | yes | Daily budget in USD |
| monthly_budget | number | – | Monthly budget in USD |
| weekly_budget | number | – | Weekly budget in USD |
No output schema declared.
No examples provided.
tokmeter_cache_efficiency ~96
Analyze cache hit/miss patterns across sessions. Shows overall cache hit rate, dollar savings from caching, cache write waste, and per-model breakdown. Use this to understand how effectively prompt caching is reducing your costs.
| Name | Type | Req | Description |
|---|---|---|---|
| period | string | – | Time period to analyze: today, week, or month |
| project | string | – | Filter by project name/path substring |
| provider | string | – | Filter to a specific provider |
No output schema declared.
No examples provided.
tokmeter_cleanup_execute ~182
DESTRUCTIVE: Permanently delete session data matching the given filters. Creates a backup by default before deleting. ALWAYS call tokmeter_cleanup_preview first. Requires confirm='DELETE' as a safety guard.
| Name | Type | Req | Description |
|---|---|---|---|
| backup | boolean | – | Create tar.gz backup before deleting (default: true) |
| confirm | string | yes | Must be exactly 'DELETE' to proceed with deletion |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
| since | string | – | Start date (YYYY-MM-DD) for custom date range |
| until | string | – | End date (YYYY-MM-DD) for custom date range |
No output schema declared.
No examples provided.
tokmeter_cleanup_preview ~151
Preview what session data would be deleted for the given filters. Shows affected files, directories, database rows, total bytes, and per-project/provider breakdown. ALWAYS call this before tokmeter_cleanup_execute to understand the impact.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
| since | string | – | Start date (YYYY-MM-DD) for custom date range |
| until | string | – | End date (YYYY-MM-DD) for custom date range |
No output schema declared.
No examples provided.
tokmeter_compare ~130
Compare two or more models or providers side-by-side on cost, tokens, efficiency, and usage metrics. Use this when the user wants to know which model or provider is cheaper, more efficient, or more heavily used.
| Name | Type | Req | Description |
|---|---|---|---|
| compare_type | string | yes | What to compare: models, providers, or projects |
| names | array | – | Specific names to compare (if omitted, compares top entries) |
| project | string | – | Filter by project name/path substring |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_cost_optimization_tips ~72
Analyze usage patterns and provide actionable cost optimization recommendations. Generates tips based on actual data — cache efficiency, model selection, conversation length, and spending distribution. Each tip includes category, severity, and estimated savings.
| Name | Type | Req | Description |
|---|---|---|---|
| period | string | – | Time period to analyze: today, week, or month |
No output schema declared.
No examples provided.
tokmeter_digest ~120
Generate a concise natural language summary of token usage — like a daily/weekly briefing. Highlights key stats, top spenders, notable trends, and actionable insights in prose form. Use this when the user wants a quick narrative overview rather than tables.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_efficiency ~123
Analyze cache hit rates, reasoning token ratios, input/output efficiency, and cost-per-token metrics. Shows how efficiently AI agents are using tokens — high cache rates mean less wasted compute. Use this to optimize costs by identifying models or projects with poor cache utilization.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_export ~139
Export token usage data as JSON, CSV, or Markdown. Returns the full data payload in the requested format. Use JSON for programmatic consumption, CSV for spreadsheets, Markdown for reports.
| Name | Type | Req | Description |
|---|---|---|---|
| data | string | – | Which data to export (default: all) |
| format | string | yes | Export format: json, csv, or markdown |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_forecast ~127
Project future AI token costs based on historical burn rates. Calculates daily/weekly/monthly averages and projects costs for the next 7, 30, and 90 days. Also shows trend direction (accelerating, decelerating, or steady). Use this for budgeting.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_heatmap ~137
Visualize activity patterns as a heatmap — see which hours of the day and days of the week have the heaviest usage. Shows both cost and token intensity. Use this to understand work patterns and peak usage times.
| Name | Type | Req | Description |
|---|---|---|---|
| metric | string | – | Heatmap metric: cost, tokens, or records (default: cost) |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_leaderboard ~147
Rank models and providers by various metrics: total cost, cost-efficiency (cost per 1M tokens), total tokens, cache efficiency, reasoning usage, and output volume. Use this to find the best value models or identify the heaviest hitters.
| Name | Type | Req | Description |
|---|---|---|---|
| entity | string | – | Rank models or providers (default: models) |
| limit | number | – | Top N to show (default: 10) |
| project | string | – | Filter by project name/path substring |
| rank_by | string | – | Ranking metric (default: cost) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_model_advisor ~95
Compare what you actually spent vs what cheaper models would have cost. Shows current spending by model and estimates savings if you downgraded expensive models (e.g., Opus → Sonnet, GPT-5 → GPT-4o). Includes a reference pricing table.
| Name | Type | Req | Description |
|---|---|---|---|
| period | string | – | Time period to analyze: today, week, or month |
| project | string | – | Filter by project name/path substring |
No output schema declared.
No examples provided.
tokmeter_models ~128
Detailed per-model cost and token breakdown with visual bar charts. Shows every model used, its provider, total tokens, cost, and share of total spend. Use this to identify which models are driving cost.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | number | – | Max models to show (default: 20) |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_projects ~108
Show per-project token usage breakdown — cost, tokens, active days, models used, and date range. Use this to see which projects are consuming the most AI resources.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | number | – | Max projects to show (default: 20) |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_providers ~97
Compare token usage across providers (Claude Code, Cursor, Codex, Gemini, etc.). Shows cost, tokens, model count, and share for each provider. Use this to understand which AI coding agents are most used and costly.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_pulse ~116
Get a quick pulse-check snapshot of token usage — total cost, tokens, active models, projects, and providers. Use this as the default first tool to understand overall AI agent spending. Supports today/week/month/all scopes.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_restore ~62
Restore session data from a cleanup backup. Requires confirm='RESTORE' as a safety guard.
| Name | Type | Req | Description |
|---|---|---|---|
| backup_id | string | yes | Backup ID to restore (from tokmeter_backups) |
| confirm | string | yes | Must be exactly 'RESTORE' to proceed |
No output schema declared.
No examples provided.
tokmeter_search ~232
Flexible search across all token usage records with filtering by model, provider, project, date range, and cost thresholds. Returns individual records sorted by timestamp. Use this to find specific usage events or investigate high-cost records.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | number | – | Max records to return (default: 25) |
| max_cost | number | – | Maximum cost per record (USD) |
| min_cost | number | – | Minimum cost per record (USD) |
| model | string | – | Filter by model name substring |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
| since | string | – | Start date (YYYY-MM-DD) for custom date range |
| sort_by | string | – | Sort by cost (desc), tokens (desc), or time (desc). Default: time |
| until | string | – | End date (YYYY-MM-DD) for custom date range |
No output schema declared.
No examples provided.
tokmeter_streaks ~111
Analyze your AI coding habits — active day streaks, weekend vs weekday usage, session frequency, and consistency metrics. Use this to understand how regularly and intensively you use AI coding agents.
| Name | Type | Req | Description |
|---|---|---|---|
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
tokmeter_timeline ~130
Show a day-by-day timeline of token usage with sparkline trends and daily cost/token breakdowns. Use this to see patterns over time — spending spikes, quiet days, and usage trends.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | number | – | Max days to show (default: 30, most recent first) |
| project | string | – | Filter by project name/path substring |
| providers | array | – | Filter to specific providers (e.g. ['claude-code','cursor']) |
| scope | string | – | Time scope: today, week (last 7d), month (calendar month), or all (default) |
No output schema declared.
No examples provided.
What is the Tokmeter — AI Agent Usage & Cost MCP server?
Tokmeter — AI Agent Usage & Cost is an MCP server listed in the public MCP registry as io.github.sriinnu/tokmeter. Tokens and cost for Claude Code, Codex and 14 more AI coding agents, from local session files. This page covers its npm package (@sriinnu/tokmeter-mcp).
Is the Tokmeter — AI Agent Usage & Cost MCP server safe to use?
Tokmeter — AI Agent Usage & Cost scores 79 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 24 September 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Tokmeter — AI Agent Usage & Cost MCP server expose?
Tokmeter — AI Agent Usage & Cost exposes 24 tools: tokmeter_pulse, tokmeter_models, tokmeter_providers, tokmeter_projects, tokmeter_timeline, and 19 more. Their descriptions and schemas cost roughly 2,875 tokens of context every time the server is loaded.
Is the Tokmeter — AI Agent Usage & Cost MCP server still maintained?
Tokmeter — AI Agent Usage & Cost is still listed as active in the MCP registry. We last reached this channel on 24 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the Tokmeter — AI Agent Usage & Cost MCP server under?
Tokmeter — AI Agent Usage & Cost declares the AGPL-3.0-only licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.