Langfuse (therealsachin) MCP Server
@therealsachin/langfuse-mcp
npm
v1.4.2
Published by @therealsachin — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
MCP server for Langfuse analytics and cost monitoring with readonly/readwrite modes via CLI flags for secure npx deployment
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 1
medium Untrusted input can drive an external actionMTC-FLOW-005
Untrusted-input tools ([get_traces]) co-exist with external-action tools ([create_comment, write_create_comment]). A prompt injection could cause unwanted external actions, though no direct sensitive-data leak path was found.
Evidence: untrusted [get_traces] → sinks [create_comment, write_create_comment]
Fix: Require confirmation for state-changing/egress actions triggered after processing untrusted content.
Location: flow get_traces → create_comment
Tools 32
Each tool and what it can reach — statically extracted from the published source.
create_commentnetwork egressget_tracesingests untrusted inputwrite_create_commentnetwork egresscreate_datasetno sensitive capabilitycreate_dataset_itemno sensitive capabilitydelete_dataset_itemno sensitive capabilityget_commentno sensitive capabilityget_cost_analysisno sensitive capabilityget_daily_metricsno sensitive capabilityget_datasetno sensitive capability
Show 22 more tools ↓
get_dataset_itemno sensitive capabilityget_health_statusno sensitive capabilityget_metricsno sensitive capabilityget_model_detailno sensitive capabilityget_observation_detailno sensitive capabilityget_observationsno sensitive capabilityget_projectsno sensitive capabilityget_prompt_detailno sensitive capabilityget_trace_detailno sensitive capabilitylist_commentsno sensitive capabilitylist_dataset_itemsno sensitive capabilitylist_datasetsno sensitive capabilitylist_modelsno sensitive capabilitylist_projectsno sensitive capabilitylist_promptsno sensitive capabilityproject_overviewno sensitive capabilitytop_expensive_tracesno sensitive capabilityusage_by_modelno sensitive capabilityusage_by_serviceno sensitive capabilitywrite_create_datasetno sensitive capabilitywrite_create_dataset_itemno sensitive capabilitywrite_delete_dataset_itemno sensitive capability
Toxic flows 1
Cross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
What this scan could not see
- Tools were statically extracted from the published source (32 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v1.4.2 latest |
A 96/100 | 1 | 1.13.0 | 2026-09-08 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan @therealsachin/langfuse-mcp --onlineOther implementations of Langfuse 4
Independent packages implementing the same tool, scanned with the same engine. Compare all 5 side by side →
Langfuse MCP server for accessing and analyzing telemetry data via natural language
MCP server that exposes the Langfuse REST API as tools — query traces, observations, sessions, scores, prompts, datasets, and metrics from any MCP client.
Langfuse MCP server with built-in analytics, multi-project routing, and Google OAuth. Token percentiles, accuracy metrics, failure detection, cost breakdowns, session analytics, latency analysis, context breach scanning — plus a hosted-remote deployment story.
JurisLM Langfuse MCP Server — Prompt Management + Traces/Observations 查詢
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