PlanExe MCP server
not respondingio.github.PlanExeOrg/planexe·v1.0.0·403 starsMCP server for generating rough-draft project plans from natural-language prompts.
403 stars
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If you have run it, two minutes of your experience saves the next person an afternoon.
PlanExe tools (11, 2 write)
write = sends, deletes, buys or postsexample_plansFreeReturns a curated list of example plans with download links for reports and zip bundles. Use this to preview what PlanExe output looks like before creating your own plan. Especially useful when the user asks what the output looks like before committing to a plan. No API key required.
example_promptsFreeCall this first. Returns example prompts that define what a good prompt looks like. Do NOT call plan_create yet. Optional before plan_create: call model_profiles to choose model_profile. Next is a non-tool step: formulate a detailed prompt (typically ~300-800 words; use examples as a baseline, similar structure) and get user approval. Good prompt shape: objective, scope, constraints, timeline, stakeholders, budget/resources, and success criteria. Write the prompt as flowing prose, not structured markdown with headers or bullet lists. Weave technical specs, constraints, and targets naturally into sentences. Include banned words/approaches and governance preferences inline. The examples demonstrate this prose style — match their tone and density. Then call plan_create. PlanExe is not for tiny one-shot outputs like a 5-point checklist; and it does not support selecting only some internal pipeline steps.
model_profilesFreeOptional helper before plan_create. Returns model_profile options with plain-language guidance and currently available models in each profile. If no models are available, returns error code MODEL_PROFILES_UNAVAILABLE.
plan_createwrite actionFreeCall only after example_prompts and after you have completed prompt drafting/approval (non-tool step). PlanExe turns the approved prompt into a strategic project-plan draft (20+ sections) in ~10-20 min. Sections include: executive summary, interactive Gantt charts, investor pitch, project plan with SMART criteria, strategic decision analysis, scenario comparison, assumptions with expert review, governance structure, SWOT analysis, team role profiles, simulated expert criticism, work breakdown structure, plan review (critical issues, KPIs, financial strategy, automation opportunities), Q&A, premortem with failure scenarios, self-audit checklist, and adversarial premise attacks that argue against the project. The adversarial sections (premortem, self-audit, premise attacks) surface risks and questions the prompter may not have considered. Returns plan_id (UUID); use it for plan_status, plan_stop, plan_retry, and plan_file_info. To track progress, poll plan_status at reasonable intervals (e.g. every 5 minutes). Optionally, run `curl -N <sse_url>` in a background shell as a completion detector — the stream auto-closes on terminal state (completed/failed/stopped). If you lose a plan_id, call plan_list to recover it. If the same prompt + model_profile is submitted by the same user within a short window, the existing plan is returned (with deduplicated=true) instead of creating a new one. If you are unsure which model_profile to choose, call model_profiles first. If your deployment uses credits, include user_api_key to charge the correct account. Common error codes: INVALID_USER_API_KEY, USER_API_KEY_REQUIRED, INSUFFICIENT_CREDITS.
plan_file_infoFreeReturns file metadata (content_type, download_url, download_size, expires_at) for the report or zip artifact. Use artifact='report' (default) for the interactive HTML report (~700KB, self-contained with embedded JS for collapsible sections and interactive Gantt charts — open in a browser). Use artifact='zip' for the full pipeline output bundle (md, json, csv intermediary files that fed the report). While the task is still pending or processing, returns {ready:false,reason:"processing"}. Check readiness by testing whether download_url is present in the response. Once ready, present download_url to the user or fetch and save the file locally. Download URLs expire after 15 minutes (see expires_at); call plan_file_info again to get a fresh URL if needed. Terminal error codes: generation_failed (plan failed), content_unavailable (artifact missing). Unknown plan_id returns error code PLAN_NOT_FOUND.
plan_listFreeList the most recent plans for an authenticated user. Returns up to `limit` plans (default 10, max 50) newest-first, each with plan_id, state, progress_percentage, created_at (ISO 8601), and a prompt_excerpt (first 100 chars). Use this to recover a lost plan_id or to review recent activity.
plan_resumeFreeResume a failed or stopped plan without discarding completed intermediary files. Plan generation restarts from the first incomplete step, skipping all steps that already produced output files. Use plan_resume when plan_status shows 'failed' or 'stopped' and plan generation was interrupted before completing all steps (network drop, timeout, plan_stop, worker crash). For a full restart or to change model_profile, use plan_retry instead. Only failed or stopped plans can be resumed. Returns PLAN_NOT_FOUND when plan_id is unknown and PLAN_NOT_RESUMABLE when the plan is not in failed or stopped state. Returns PIPELINE_VERSION_MISMATCH when the snapshot was created by a different pipeline version; use plan_retry instead.
plan_retryFreeRetry a plan that is currently in failed or stopped state. Pass the plan_id and optionally model_profile (defaults to baseline). The plan is reset to pending, prior artifacts are cleared, and the same plan_id is requeued for processing. Returns PLAN_NOT_FOUND when plan_id is unknown and PLAN_NOT_FAILED when the plan is not in failed or stopped state.
plan_statusFreeReturns status and progress of the plan currently being created. This is the primary way to check progress — it returns structured JSON with all progress fields. Poll at reasonable intervals (e.g. every 5 minutes): plan generation typically takes 10-20 minutes (baseline profile) and may take longer on higher-quality profiles. State contract: pending/processing => keep polling; completed => download is ready; failed => terminal error; stopped => user called plan_stop (consider plan_resume). progress_percentage is 0-100 (integer-like float); 100 when completed. Note: steps vary in duration — early steps complete quickly while later steps (review, report generation) take longer. Do not use progress_percentage to estimate time remaining. steps_completed and steps_total give the number of plan generation steps completed and expected (both nullable). current_step is the human-readable label of the most recently completed step (e.g. 'SWOT Analysis'). timing.last_progress_at is an ISO 8601 timestamp of the last progress update (null until the first worker update); use it to compute time-since-last-progress and detect stalls — a gap > 10 minutes with no progress change is a strong stall signal. files lists the most recent 10 intermediate outputs produced so far (files_count gives the total); use their updated_at timestamps as a secondary stall signal. When state is 'failed', the response includes an error dict with failure diagnostics: error.failure_reason (category: generation_error, worker_error, inactivity_timeout, internal_error, version_mismatch), error.failed_step (pipeline step active at failure), error.message (human-readable message), and error.recoverable (true => plan_resume may work, false => use plan_retry). The error dict is absent for non-failed states. Unknown plan_id returns error code PLAN_NOT_FOUND. Troubleshooting: pending for >5 minutes likely means queued but not picked up by a worker. processing with timing.last_progress_at unchanged for >10 minutes likely means stalled — call plan_stop then plan_retry. Fall back to file updated_at timestamps if last_progress_at is null. Report these issues to https://github.com/PlanExeOrg/PlanExe/issues .
plan_stopFreeRequest the plan generation to stop. Pass the plan_id (the UUID returned by plan_create). Stopping is asynchronous: the stop flag is set immediately but the plan may continue briefly before halting. A stopped plan will transition to the stopped state. If the plan is already completed or failed, stop_requested returns false (the plan already finished). Unknown plan_id returns error code PLAN_NOT_FOUND.
send_feedbackwrite actionFreeSubmit feedback about PlanExe — issues, impressions, or suggestions. Callable at any point in the workflow; fire-and-forget, never blocks. Use category to classify: mcp (MCP tools, SSE, plan_status, workflow), plan (the generated output files), code (PlanExe source), docs (documentation), other. Optionally attach to a plan via plan_id. Use rating (1-5) for sentiment: 1=strong negative, 3=neutral, 5=strong positive. Especially useful for reporting: SSE streams that close before plan completion, plan_status returning stale or inconsistent data, queue delays where workers are slow to pick up plans, and impressions of plan output quality after reviewing reports. Include specific details (plan_id, percentages, timestamps) when reporting issues.
Public scan report
scanner v0.1.10 · 2026-10-14 · same rubric, same numbers if you re-run it
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote unreachable: TypeError: fetch failed0/20
- –Tool poisoningtools not inspected (endpoint requires auth); not countedn/a
- Auth qualityAPI key sent as a header8/15
- Maintenancelast push 3 days ago15/15
- Maintainer identityregistry namespace matches repository owner7/10
Findings (1)
- highRemote endpoint did not respond
reliability.unreachableTypeError: fetch failed
How PlanExe compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 50/100
- higher than 9% of 48,114 servers
- Tools
- 11
- the typical server has 7
- Tools that change things
- 18%
- typical: 0%. Fewer write tools means less an agent can break
- Uptime
- 0%
- of our recent checks; the typical remote server answers 100%
- Response time
- 248 ms
- faster than 50% of 30,044 servers
- GitHub stars
- 403
- more than 95% of 28,851 servers
What its tools let an agent do: 9 read · 1 change · 1 send or post
Install PlanExe in Claude Code, Cursor or VS Code
claude mcp add --transport http planexe https://mcp.planexe.org/mcp
What the publisher says
From the PlanExe repository's README, as published. We do not edit it. Read it on GitHub
Planning complex projects should not require a consulting-firm budget.
Turn a complex project brief into an editable planning baseline in about 15 minutes.
Create an account | See example plans | Getting started guide
Why PlanExe exists
Good ideas are not limited to people and organizations that can afford a large consulting engagement. Turning an ambitious idea into a coherent project, however, normally requires substantial time, specialist knowledge, stakeholder interviews, and repeated synthesis.
PlanExe is open-source software for people and AI agents that need to plan complex projects. Describe a project in plain language and PlanExe creates a structured first-pass plan: the assumptions to challenge, decisions to make, work to coordinate, risks to investigate, and questions that must be answered before execution.
The result is not a substitute for stakeholder participation or professional sign-off. It is a way to begin with a broad, inspectable planning baseline instead of a blank page.
What PlanExe does
PlanExe examines a project from several planning perspectives and combines the results into one self-contained interactive report. Depending on the project, the output commonly includes:
- Executive summary and project purpose
- Assumptions, constraints, and unanswered questions
- Strategic choices and alternative scenarios
- Work breakdown structure and dependency-aware Gantt chart
- Governance bodies, decision rights, and escalation paths
- Roles, stakeholders, and engagement approaches
- Risk register, SWOT analysis, and mitigation proposals
- Premortem, expert criticism, premise attack, and self-audit
- Documents to create, documents to find, and data to collect
- An editable bundle of Markdown, JSON, and CSV source artifacts
The planning pipeline can use cloud models or run with local models so sensitive project material can remain on systems you control.
Built for complex projects
PlanExe is intended for consulting-scale, multi-phase initiatives—not everyday task lists or small personal projects.
Examples of suitable work include:
it has access to specialist advisers
- Planning a regional clean-water, energy, or transport infrastructure program
- Coordinating a regulated healthcare or financial-services transformation
- Designing a cross-border public-sector initiative
- Preparing a complex business, industrial, or technology program
- Structuring an ERP migration, corporate separation, or post-merger integration
- Helping an under-resourced organization develop an ambitious proposal before
The richer the brief—objective, location, constraints, stakeholders, resources, timeline, and success criteria—the more useful the resulting plan becomes.
A plan you can inspect and change
PlanExe does not hide the planning process inside a chat transcript. Each run produces a folder of readable source artifacts alongside the final report.
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Grade history
- 2026-10-14downgradeB → Dscore 50: Remote endpoint did not respond
PlanExe: common questions
- Is PlanExe MCP server safe?
- Not recommended: it is graded D (50/100). Read the PlanExe safety report
- How do I install PlanExe?
- It runs remotely at mcp.planexe.org. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does PlanExe need an API key?
- Yes. The registry entry asks for
X-API-Key. - Is PlanExe maintained?
- The last commit was 36 days ago (2026-10-11). The latest release is v1.0.0.
- Is PlanExe up?
- 0% of our last 28 checks got an answer. We check remote servers about four times a day.
- How does PlanExe compare with other MCP servers?
- safety score 50/100 (higher than 9% of 48,114 servers); tools 11 (the typical server has 7); tools that change things 18% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.