{"$schema":"https://verifymcp.io/schemas/trust-report.json","schemaVersion":1,"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"generatedAt":"2026-11-05T16:25:12.212Z","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp","markdownUrl":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp.md","server":{"slug":"pouriaetab-llmledger","name":"io.github.pouriaetab/llmledger","registryName":"io.github.pouriaetab/llmledger","description":"Which AI model, and what it costs: LiteLLM prices, Arena ratings and price history.","registryStatus":"active","deletedAt":null,"statusMessage":null,"liveness":"live","publisher":{"class":"unknown","claimed":false}},"component":{"slug":"llmledger-mcp","type":"pypi","identifier":"llmledger-mcp","withdrawn":false,"url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp","version":"0.2.0","transport":"stdio","scoredAt":"2026-11-05T09:18:39.963Z"},"score":{"total":71,"tier":"medium","status":"scored","weekDelta":3,"history":[{"date":"2026-11-05","total":71},{"date":"2026-11-04","total":86},{"date":"2026-11-03","total":86},{"date":"2026-11-02","total":85},{"date":"2026-11-01","total":85},{"date":"2026-10-31","total":84},{"date":"2026-10-30","total":69},{"date":"2026-10-29","total":68},{"date":"2026-10-28","total":83},{"date":"2026-10-27","total":82},{"date":"2026-10-26","total":82},{"date":"2026-10-25","total":66},{"date":"2026-10-24","total":66},{"date":"2026-10-23","total":68},{"date":"2026-10-22","total":68},{"date":"2026-10-21","total":57},{"date":"2026-10-20","total":80},{"date":"2026-10-19","total":65},{"date":"2026-10-18","total":66}]},"categories":[{"name":"Supply Chain Security","score":40,"verdict":"fail","reasons":["Malware scan not yet available for this package.","CVE check failed: a known medium-severity CVE affects fastmcp 4.1.0, a direct dependency. A fixed version is available.","Runs hatchling.build at install time, a recognised build step with no custom scripting around it.","1 of 15 dependencies flagged as unhealthy."],"codes":[{"code":"supplychain.malware_inconclusive","args":{"reason":"vendor_no_verdict"}},{"code":"cve.direct","args":{"package":"fastmcp","version":"4.1.0","severity":"medium"}},{"code":"installscript.allowlisted","args":{"tool":"hatchling.build","hooks":"build_backend"}},{"code":"dephealth.assessed","args":{"deps":"15","unhealthy":"1"}}]},{"name":"Provenance & Transparency","score":97,"verdict":"fail","reasons":["Source repository is publicly reachable at the declared URL.","Cryptographically verified build provenance (signed, bound to pouriaetab/llmledger).","Clear OSI-approved license (MIT).","Actively maintained (last published 14 days ago).","Disclosure check failed: no security disclosure policy was found in the source repository."],"codes":[{"code":"provenance.repo_verified","args":{}},{"code":"provenance.verified","args":{"repo":"pouriaetab/llmledger"}},{"code":"license.osi","args":{"spdx":"MIT"}},{"code":"maintenance.recent","args":{"age_days":"14"}},{"code":"disclosure.absent","args":{}}]},{"name":"Schema Quality & AI Usability","score":76,"verdict":"fail","reasons":["100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).","AI-judged instruction clarity (good).","Context-footprint check failed: tool/resource definitions use about 2558 tokens (~213/item across 12 items; 11 tools + 1 resources), over budget; trim descriptions and params.","Usage-examples check failed: none of the tools include examples."],"codes":[{"code":"schema.descriptions","args":{"pct":"100"}},{"code":"schema.ai_quality","args":{"band":"good"}},{"code":"schema.footprint_heavy","args":{"avg":"213","items":"12","tools":"11","tokens":"2558","resources":"1"}},{"code":"schema.examples_absent","args":{}}]},{"name":"Stability & Change Management","score":60,"verdict":"partial","reasons":["Stability observed for 18 of 30 days with no destabilising changes; credit accrues until the full window elapses."],"codes":[{"code":"stability.building_history","args":{"days":"18"}}]},{"name":"Tool Coverage","score":100,"verdict":"pass","reasons":["100% of tools have a non-trivial description (not blank, and not just the tool's name).","100% of tool parameters carry a description.","Structured output schemas are declared (100% of tools); any adoption earns full credit."],"codes":[{"code":"toolquality.descriptions","args":{"pct":"100"}},{"code":"toolquality.param_docs","args":{"pct":"100"}},{"code":"toolquality.output_present","args":{"pct":"100"}}]},{"name":"Tool Safety","score":100,"verdict":"pass","reasons":["No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.","We read all 11 captured tool definition(s), and no name or description among them implies an irreversible operation.","An AI judge read all 13 captured unit(s) of tool text and found none that tries to manipulate the model reading it."],"codes":[{"code":"toolsafety.injection_clean","args":{}},{"code":"toolsafety.destructive_none","args":{"tools":"11"}},{"code":"toolsafety.manipulation_clean","args":{"units":"13","judged":"13"}}]},{"name":"Capabilities","score":100,"verdict":"pass","reasons":["Implements a current MCP spec version (2026-07-28)."],"codes":[{"code":"protocol.current","args":{"version":"2026-07-28"}}]}],"inconclusive":["Malware scan not yet available for this package."],"malware":[],"components":[{"slug":"llmledger-mcp","type":"pypi","identifier":"llmledger-mcp","withdrawn":false,"score":71,"current":true,"url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp","markdownUrl":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp.md"}],"facts":[{"label":"Registry","value":"pypi"},{"label":"Package","value":"llmledger-mcp"},{"label":"Version","value":"0.2.0"},{"label":"Transport","value":"stdio"}],"install":{"available":true,"bundleSha256":null},"tools":[{"name":"find_models","title":"Find Models","description":"List the highest rated models for a kind of work within price, prompt size, ability and maker limits, each\nat its cheapest listing with its rating; or, with `name`, look one model up and list every host that offers\nit. Use when browsing or filtering the catalogue, or to find a model's exact name. Not for choosing between\nnamed models (compare_models), for a prompt you have in hand (suggest_for_project), or for a budget\n(estimate_cost).","inputs":[{"name":"limit","type":"integer","required":false,"description":"How many models to list (up to 200 for the whole catalogue)"},{"name":"maker","type":null,"required":false,"description":"Only this maker, for example anthropic or openai"},{"name":"max_output_price","type":null,"required":false,"description":"Highest answer price, dollars per 1M tokens"},{"name":"min_context","type":null,"required":false,"description":"Smallest prompt size the model must take, in tokens"},{"name":"name","type":null,"required":false,"description":"Look up one model by name instead of browsing: all its listings"},{"name":"needs","type":"array","required":false,"description":"What the model must be able to do"},{"name":"task","type":"string","required":false,"description":"The kind of work, as Arena rates it"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":227},{"name":"compare_models","title":"Compare Models","description":"Compare 2 to 6 named models for a kind of work: rating, prices, cost per task (or how fast each uses a\nClaude or ChatGPT plan), the pick, and for each model the share of answer tokens at which it would beat the\npick. Use when the user already has candidate models in mind. Not for finding candidates (find_models), for\nreading a prompt to guess the work (suggest_for_project), or for a monthly budget (estimate_cost).","inputs":[{"name":"answer_tokens","type":null,"required":false,"description":"Answer tokens per model when they differ, by the names given"},{"name":"input_tokens","type":"integer","required":false,"description":"Prompt tokens per task"},{"name":"models","type":"array","required":true,"description":"2 to 6 model names, for example claude-opus-5.5, gpt-6.1-sol"},{"name":"output_tokens","type":"integer","required":false,"description":"Answer tokens per task, including hidden thinking"},{"name":"pay","type":"string","required":false,"description":"api: dollars; claude or chatgpt: how fast each uses that plan"},{"name":"task","type":"string","required":false,"description":"The kind of work, as Arena rates it"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":225},{"name":"estimate_cost","title":"Estimate Cost","description":"Price a workload on 1 to 10 models at each one's cheapest listing: dollars per call, per day and per 30\ndays, and with cache tokens the saving the cache makes. Use when the question is a budget or a bill: token\ncounts and calls a day are known. Not for deciding which model is better (compare_models) or for pricing\npast usage from an export (price_my_usage).","inputs":[{"name":"cache_write_tokens","type":"integer","required":false,"description":"How many of the prompt tokens are written to the cache"},{"name":"cached_tokens","type":"integer","required":false,"description":"How many of the prompt tokens are read from the cache"},{"name":"calls_per_day","type":"number","required":false,"description":"Calls per day"},{"name":"input_tokens","type":"integer","required":true,"description":"Prompt tokens per call"},{"name":"models","type":"array","required":true,"description":"1 to 10 model names"},{"name":"output_tokens","type":"integer","required":true,"description":"Answer tokens per call, including hidden thinking"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":186},{"name":"price_history","title":"Price History","description":"Show one model's price history: every price and retirement date change since 2023 on every host, each\nwith the LiteLLM change behind it, the chance of a price change, retirement or removal in the next 90 days\nand year, and with `date`, the prices on that day. Use when the question is about one model over time, a\npast price, or how likely a price is to move. Not for today's cheapest price of several models (find_models\nor estimate_cost).","inputs":[{"name":"date","type":null,"required":false,"description":"A day as YYYY-MM-DD: each listing's prices that day and the change that set them"},{"name":"model","type":"string","required":true,"description":"A model name, for example claude-opus-5.5, or one listing such as bedrock/anthropic.claude-opus-5-5"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":177},{"name":"suggest_for_project","title":"Suggest For Project","description":"Suggest a model and effort level for a prompt or a described project: it guesses the kind of work and\nnames the best value (the cheapest model the votes cannot tell apart from the top), the top rated and the\ncheapest rated, each with its cost per task. Use when the user asks \"which model should I use for this\" and\nthe work itself is in hand. Not for named candidates (compare_models) or for browsing by limits\n(find_models).","inputs":[{"name":"answer","type":"string","required":false,"description":"Typical answer length"},{"name":"pay","type":"string","required":false,"description":"api: dollars; claude or chatgpt: compare within that plan"},{"name":"prompt","type":"string","required":true,"description":"The project's starting prompt, or a description of the work"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":155},{"name":"not_yet_priced","title":"Not Yet Priced","description":"List the models Arena has rated that LiteLLM's catalogue does not price yet, with how soon the catalogue\nusually prices a maker's models after Arena first shows them. Use when a brand-new model is missing from the\nother tools' answers, or to ask what is coming. Not for models that already have a price (find_models).","inputs":[{"name":"maker","type":null,"required":false,"description":"Only this maker, for example meta or ibm"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":96},{"name":"estimate_time","title":"Estimate Time","description":"Estimate how long one call and a whole job take, as a usual time and a slow day, from the user's own timed\nruns of that model called that way (kept by log_run). Use when the question is time, not money, and some\nruns have been logged; it says so when none have. Not for cost (estimate_cost) or for a job you have a\npromptfoo sample of (forecast_job gives time and cost together).","inputs":[{"name":"calls","type":"integer","required":false,"description":"How many calls the job makes"},{"name":"concurrency","type":"integer","required":false,"description":"Calls running at once"},{"name":"input_tokens","type":"integer","required":true,"description":"Prompt tokens per call"},{"name":"model","type":"string","required":true,"description":"A model name, as the catalogue or Ollama names it"},{"name":"output_tokens","type":"integer","required":true,"description":"Answer tokens per call, including hidden thinking"},{"name":"thinking","type":"boolean","required":false,"description":"Thinking turned on"},{"name":"way","type":"string","required":false,"description":"How the model is called"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":194},{"name":"log_run","title":"Log Run","description":"Record a timed run (model, tokens, seconds, how it was called), or every result of a promptfoo results\nfile, in a file on this computer so estimate_time can learn from it. Use right after a call or a promptfoo\nrun whose time is known. Not a query: it stores and returns what it stored. Nothing is sent anywhere.","inputs":[{"name":"input_tokens","type":null,"required":false,"description":"Prompt tokens of the call"},{"name":"model","type":null,"required":false,"description":"The model that ran"},{"name":"output_tokens","type":null,"required":false,"description":"Answer tokens of the call, hidden thinking included"},{"name":"promptfoo_results","type":null,"required":false,"description":"Path of a promptfoo results file (promptfoo eval -o results.json): every result becomes a run"},{"name":"seconds","type":null,"required":false,"description":"How long the call took"},{"name":"task","type":null,"required":false,"description":"The kind of work, if known"},{"name":"thinking","type":"boolean","required":false,"description":"Thinking was on (a promptfoo result that counts thinking tokens is marked on by itself)"},{"name":"way","type":null,"required":false,"description":"How the model was called (default api; for a promptfoo file, read from each provider)"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":215},{"name":"forecast_job","title":"Forecast Job","description":"Estimate a whole job's time, cost and accuracy from a promptfoo run of a sample of it: for each model in\nthe sample, the time as a usual time and a slow day, the cost at its cheapest listing next to the listing the\nsample used, the 90-day chance of a price change, how often it was right (95% range) and the break-even\nagainst the pick. Use when a promptfoo results file of a sample exists and the whole job's size is known.\nNot for a job with no sample (estimate_cost for money, estimate_time for time).","inputs":[{"name":"concurrency","type":null,"required":false,"description":"Calls running at once in the whole job (default: as the sample ran)"},{"name":"items","type":"integer","required":true,"description":"How many tests the whole job has"},{"name":"promptfoo_results","type":"string","required":true,"description":"Path of a promptfoo results file from a sample of the job (promptfoo eval --filter-sample 20 -o sample.json)"},{"name":"thinking","type":"boolean","required":false,"description":"Thinking turned on"},{"name":"way","type":null,"required":false,"description":"How the models are called (default: read from each provider)"},{"name":"wrong_answer_cost","type":null,"required":false,"description":"Dollars a wrong answer costs you to catch and fix; the pick then counts it"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":250},{"name":"local_or_cloud","title":"Local Or Cloud","description":"Compare running an open model on a computer you buy with paying a cloud model per call: the cost a month\neach way, the month the computer pays for itself, and whether it keeps up with the load. Use when the\nquestion is whether to buy hardware for a local model. Needs timed runs of the local model (log_run) and the\ncomputer's price; electricity comes from EIA or the user's own rate. Not for cloud-only comparisons\n(compare_models or estimate_cost).","inputs":[{"name":"cached_tokens","type":"integer","required":false,"description":"Prompt tokens read from the cloud model's cache"},{"name":"calls_per_month","type":"number","required":true,"description":"Calls a month"},{"name":"cloud_models","type":"array","required":true,"description":"1 to 5 cloud models to compare with"},{"name":"electricity_price","type":null,"required":false,"description":"Your electricity price, dollars per kWh (default: EIA's average for homes)"},{"name":"hardware_price","type":"number","required":true,"description":"What the computer costs you, in dollars"},{"name":"input_tokens","type":"integer","required":true,"description":"Prompt tokens per call"},{"name":"local_model","type":"string","required":true,"description":"The open model you would run at home, as Ollama names it, for example llama3.1:8b"},{"name":"local_way","type":"string","required":false,"description":"How the local model is called"},{"name":"months","type":"integer","required":false,"description":"How many months to compare over"},{"name":"output_tokens","type":"integer","required":true,"description":"Answer tokens per call, including hidden thinking"},{"name":"state","type":null,"required":false,"description":"A US state, for EIA's average there, for example Texas"},{"name":"thinking","type":"boolean","required":false,"description":"Thinking turned on for the local model"},{"name":"watts","type":null,"required":false,"description":"Power the computer draws while it answers, in watts"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":329},{"name":"price_my_usage","title":"Price My Usage","description":"Price the user's own past coding agent usage, from a ccusage or codeburn export, on every rated model:\neach session at the price of its day, the models that keep the rating and cost less, a 95% range for the cost\nper session, and whether two models differ for real or the data cannot tell. Use when a usage export (or a\nlist of token mixes) exists and the question is what the same work would have cost elsewhere. Not for a\nfuture workload (estimate_cost) or for a prompt (suggest_for_project). Reads token counts, names and dates\nonly; nothing leaves the computer.","inputs":[{"name":"compare","type":null,"required":false,"description":"Two models to test against each other on the same sessions"},{"name":"export","type":null,"required":false,"description":"Path of a token export on this computer: `ccusage daily --json > f.json`, `ccusage session --json > f.json`, or `codeburn export -f json -o f.json`"},{"name":"limit","type":"integer","required":false,"description":"How many models to list in every_model (the cheapest first)"},{"name":"mix","type":null,"required":false,"description":"Instead of a file: token mixes as {model, date, input, output, cache_read, cache_write, session?}"},{"name":"task","type":null,"required":false,"description":"The kind of work the sessions were (default: codeburn's categories, else coding)"}],"outputs":[],"hasOutputSchema":true,"hasExamples":false,"tokenEstimate":271}],"toolsTruncatedAtCapture":false,"diagnostics":{"capturedAt":"2026-11-05T09:18:39.000Z","track":"package","endpoint":null,"declaredUrl":null,"truncated":false,"tls":null,"dnssec":null,"auth":null,"httpsRedirect":null,"transports":[],"provenance":{"outcome":"verified","label":"Verified","reason":"verified","reasonLabel":"Verified","discovery":"attestation_endpoint","discoveryLabel":"Registry attestation endpoint","sourceRepo":null,"attestationSkipped":null,"attestationSkippedLabel":null},"installScripts":[{"hook":"build_backend","tier":"allowlisted"}],"installScriptsTotal":null,"vulnerabilities":[{"id":"GHSA-7xgj-8392-5q4r","cve":null,"severity":"medium","fixAvailable":true},{"id":"GHSA-vqqp-x5qm-5qp4","cve":null,"severity":"medium","fixAvailable":true}],"vulnerabilitiesTotal":2,"dependencies":{"nodes":15,"partial":false,"deprecated":null,"stale":1,"noRepo":null}},"mismatches":[],"changelog":{"trackingSince":"2026-10-18","recent":[{"id":"chg_01a1ab00-d176-754a-b03f-082b80ccb938","kind":"check.unverifiable","summary":"Malware scan (pass → unverified)","materiality":"security","direction":"regression","scoreDelta":null,"occurredOn":"2026-11-05","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1ab00-d176-754a-b03f-082b80ccb938"},{"id":"chg_01a1ab00-d177-782a-aa37-68b19792b73a","kind":"score.total_changed","summary":"Trust score (86 → 71)","materiality":"functional","direction":"regression","scoreDelta":-15,"occurredOn":"2026-11-05","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1ab00-d177-782a-aa37-68b19792b73a"},{"id":"chg_01a1a0b7-1eb5-747c-b708-d8c0cf12ee53","kind":"score.total_changed","summary":"Trust score (85 → 86)","materiality":"functional","direction":"improvement","scoreDelta":1,"occurredOn":"2026-11-03","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1a0b7-1eb5-747c-b708-d8c0cf12ee53"},{"id":"chg_01a195c4-0bbc-76ba-8ee8-3c46edae6144","kind":"score.total_changed","summary":"Trust score (84 → 85)","materiality":"functional","direction":"improvement","scoreDelta":1,"occurredOn":"2026-11-01","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a195c4-0bbc-76ba-8ee8-3c46edae6144"},{"id":"chg_01a1909b-cb87-785d-82ec-d66eb9219418","kind":"check.reverified","summary":"Malware scan (unverified → pass)","materiality":"security","direction":"improvement","scoreDelta":null,"occurredOn":"2026-10-31","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1909b-cb87-785d-82ec-d66eb9219418"},{"id":"chg_01a1909b-cb89-716c-b28e-609edc6ccd0f","kind":"score.total_changed","summary":"Trust score (69 → 84)","materiality":"functional","direction":"improvement","scoreDelta":15,"occurredOn":"2026-10-31","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1909b-cb89-716c-b28e-609edc6ccd0f"},{"id":"chg_01a18c1e-cd0d-78a0-8a4d-2b2b6e1e1292","kind":"score.total_changed","summary":"Trust score (68 → 69)","materiality":"functional","direction":"improvement","scoreDelta":1,"occurredOn":"2026-10-30","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a18c1e-cd0d-78a0-8a4d-2b2b6e1e1292"},{"id":"chg_01a186f6-dbbe-7ebe-8672-6375140b79fd","kind":"check.unverifiable","summary":"Malware scan (pass → unverified)","materiality":"security","direction":"regression","scoreDelta":null,"occurredOn":"2026-10-29","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a186f6-dbbe-7ebe-8672-6375140b79fd"},{"id":"chg_01a186f6-dbc0-7767-9cb9-e5d132151cc5","kind":"score.total_changed","summary":"Trust score (83 → 68)","materiality":"functional","direction":"regression","scoreDelta":-15,"occurredOn":"2026-10-29","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a186f6-dbc0-7767-9cb9-e5d132151cc5"},{"id":"chg_01a1811d-6b5e-738c-84ce-ba0680dcfb8c","kind":"score.total_changed","summary":"Trust score (82 → 83)","materiality":"functional","direction":"improvement","scoreDelta":1,"occurredOn":"2026-10-28","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1811d-6b5e-738c-84ce-ba0680dcfb8c"},{"id":"chg_01a1770f-4e0e-7dc2-a7ed-1158abf5c640","kind":"check.reverified","summary":"Malware scan (unverified → pass)","materiality":"security","direction":"improvement","scoreDelta":null,"occurredOn":"2026-10-26","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1770f-4e0e-7dc2-a7ed-1158abf5c640"},{"id":"chg_01a1770f-4e10-7058-a4b7-269e360b3d03","kind":"score.total_changed","summary":"Trust score (66 → 82)","materiality":"functional","direction":"improvement","scoreDelta":16,"occurredOn":"2026-10-26","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a1770f-4e10-7058-a4b7-269e360b3d03"},{"id":"chg_01a16d28-6445-7e01-966d-41bf3c5fc4d3","kind":"advisory.identified","summary":"GHSA-vqqp-x5qm-5qp4 affects this package (medium)","materiality":"security","direction":"regression","scoreDelta":null,"occurredOn":"2026-10-24","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a16d28-6445-7e01-966d-41bf3c5fc4d3"},{"id":"chg_01a16d28-6446-7efe-ae43-a91b0fa2bff2","kind":"advisory.identified","summary":"GHSA-7xgj-8392-5q4r affects this package (medium)","materiality":"security","direction":"regression","scoreDelta":null,"occurredOn":"2026-10-24","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a16d28-6446-7efe-ae43-a91b0fa2bff2"},{"id":"chg_01a16d28-6447-75e3-863c-dbfbd3320784","kind":"check.verdict","summary":"Known CVEs (pass → fail)","materiality":"security","direction":"regression","scoreDelta":null,"occurredOn":"2026-10-24","url":"https://verifymcp.io/servers/pouriaetab-llmledger/llmledger-mcp#chg-chg_01a16d28-6447-75e3-863c-dbfbd3320784"},{"id":"chg_01a16d28-6447-7ce6-a673-99e8b96b6daf","kind":"score.total_changed","summary":"Trust score (68 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