mcp-task-tools (rog0x/mcp-task-tools) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 5 tools. No publisher has claimed this listing.

C
Emerging
74/100

mcp-task-tools

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

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Who stands behind it

rog0x

Source: Glama

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Install from

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// tools this server exposes5 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

todo_manager

Manage an in-memory task list. Add, complete, update status, delete, and list tasks. Supports filtering by status, priority, and tags. Persistent within session.

priority_sorter

Sort and prioritize tasks using proven frameworks: Eisenhower matrix (urgent/important quadrants), RICE scoring (reach, impact, confidence, effort), or MoSCoW method (must/should/could/wont).

time_estimator

Estimate task duration using PERT methodology. Break a task into subtasks, provide optimistic/realistic/pessimistic estimates for each. Returns weighted expected time plus configurable buffer.

standup_generator

Generate a daily standup update from the current task list. Shows yesterday (recently completed), today (in progress), and blockers. Uses data from todo_manager.

burndown_calculator

Calculate sprint burndown chart data. Given tasks with story points and sprint duration, computes ideal vs actual burndown, velocity metrics, and completion forecast.

// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

5/5 tools missing one or more hints — todo_manager (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); priority_sorter (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); time_estimator (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +2 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tests exist

No test files found

Add tests that exercise each declared tool.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 3 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
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commit: 9a5c848f7d391b72b6d1fdf1c2f75e4551c5d499
code hash: da67790c801c53e94a7855d4cb9cbe155a9a4fabc5ea97b25d93e0cc552700e6
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