Harvest Forecast MCP Server
harvest-forecast-mcp
PyPI
v0.1.1
Published by azx-pbc-oss — 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 Harvest and Forecast APIs — let AI agents track time, manage projects, and update scheduling.
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 − 1 = 99. 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 |
|---|---|
| −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 0
Tools 34
Each tool and what it can reach — statically extracted from the published source.
all_projects_scheduleno sensitive capabilitybudget_statusno sensitive capabilitycreate_assignmentno sensitive capabilitycreate_time_entryno sensitive capabilitydelete_assignmentno sensitive capabilityforecast_whoamino sensitive capabilityget_assigned_peopleno sensitive capabilityget_forecast_personno sensitive capabilityget_forecast_projectno sensitive capabilityget_future_scheduled_hoursno sensitive capability
Show 24 more tools ↓
get_future_scheduled_hours_for_projectno sensitive capabilityget_person_heatmapno sensitive capabilityget_placeholder_heatmapno sensitive capabilityget_project_heatmapno sensitive capabilityget_remaining_budgeted_hoursno sensitive capabilityharvest_whoamino sensitive capabilitylist_assignmentsno sensitive capabilitylist_forecast_milestonesno sensitive capabilitylist_forecast_peopleno sensitive capabilitylist_forecast_placeholdersno sensitive capabilitylist_forecast_projectsno sensitive capabilitylist_forecast_rolesno sensitive capabilitylist_harvest_clientsno sensitive capabilitylist_harvest_projectsno sensitive capabilitylist_harvest_tasksno sensitive capabilitylist_harvest_usersno sensitive capabilitylist_project_assignmentsno sensitive capabilitylist_time_entriesno sensitive capabilityperson_scheduleno sensitive capabilityproject_overviewno sensitive capabilityteam_utilizationno sensitive capabilitytime_summaryno sensitive capabilityupdate_assignmentno sensitive capabilitywho_is_availableno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (34 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 2
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 |
|---|---|---|---|---|
v0.1.1 latest |
A 99/100 | 0 | 1.13.0 | 2026-08-25 |
v0.1.0 |
A 98/100 | 1 | 1.5.0 | 2026-07-22 |
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.
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