WSAI FixCenter
Evidence-first MCP server for diagnosing problems with hooks, plugins, skills and configuration, returning ranked probable causes and reviewable fixes without modifying the workspace.
README
wsai_fckdot
wsai_fckdot is a public, privacy-first MCP server for diagnosing hooks, plugins, skills, MCP integrations, configuration, runtimes, networking and PC system state. It also turns a chaotic multi-agent setup into one canonical manifest, isolated account profiles and generated adapters for each supported tool.
It never repairs a machine automatically, never interpolates user input into commands, never elevates privileges and never sends telemetry. Account bindings accept environment-variable references rather than values; common credential-shaped text is rejected, but users must still keep secrets out of free-form instructions. Setup files are written only after a reviewed plan and explicit consent.
Verified scope
- 38 read-only controls in 12 domains;
- 100% catalog design coverage on Windows, Linux and macOS;
- 15 diagnostic rule families;
- 16 synthetic evaluation cases with a 100% success gate;
- 10 MCP tools;
- 100% Python statement coverage enforced in CI;
- tested redaction of common sensitive formats and explicit execution consent.
- compatibility with both legacy MCP handshakes and the stateless
2026-07-28era. - one canonical
.wsai_fckdot/setup.jsonformat, five tool adapters and secret-free account profile activators.
The meaning of “100%” is precise. Design coverage means every declared catalog control has a probe on every supported platform. Runtime coverage means every requested probe completed successfully on one execution. Neither metric claims that every possible future application or peripheral is known. See the coverage model.
MCP tools
| Tool | Purpose | Reads the PC by default? |
|---|---|---|
diagnose |
Rank causes and propose least-invasive corrections | No |
list_diagnostics |
List the 15 diagnostic rule families | No |
get_control_catalog |
Browse the 38 controls | No |
audit_coverage |
Measure catalog design coverage | No |
collect_context |
Plan or execute selected read-only probes | Plan only |
run_self_test |
Run public synthetic regression cases | No |
get_setup_catalog |
Explain adapters, profiles and precedence | No |
inspect_setup |
Inventory setup metadata, never variable values | No, until consent |
plan_setup |
Compare a canonical manifest and preserve conflicts | No, until consent |
apply_setup |
Apply the exact reviewed plan | Yes, explicit consent |
collect_context executes only when both execute=true and consent=true. Output is excluded unless include_output=true; included output is passed through the tested redactor and truncated. As with any pattern-based redaction, review it before sharing.
One setup instead of endless .xxx folders
wsai_fckdot uses .wsai_fckdot/setup.json as the project source of truth. Write instructions once, declare account profiles using environment-variable references, and select the adapters your tools need. It can generate:
AGENTS.md;.cursor/rules/wsai_fckdot.mdc;CLAUDE.md;GEMINI.md;.github/copilot-instructions.md;- PowerShell and POSIX-shell profile activators under
.wsai_fckdot/profiles/.
The activators contain no secrets. They clear declared target variables before mapping the chosen profile from references such as env:OPENAI_WORK_API_KEY, preventing personal and work account state from remaining mixed in one shell.
wsai_fckdot inventories known tool directories and counts unknown dot-directories. Unknown names are hidden by default. It does not delete or move any .xxx directory, does not follow setup symlinks during inventory, and refuses to overwrite an existing adapter file unless it starts with an exact wsai_fckdot ownership header.
The workflow is deliberately simple:
- inspect metadata;
- create a canonical manifest;
- review a plan containing
create,update,retire,unchangedandblockedactions; - apply that exact plan ID with explicit consent;
- activate the selected account profile and restart active agent sessions.
Read the complete setup governance guide and start from setup.example.json.
Covered domains
System identity, time and locale; CPU, memory and devices; storage; processes, services, startup and scheduled tasks; environment and PATH; log availability; adapters, DNS, proxy and listeners; permissions, firewall, certificates, protection and policies; package managers, language runtimes, shells, Git and editors; MCP, hooks, plugins, skills, Codex runtime, remote-control prerequisites and chat streaming; containers and guest environments; update visibility.
Installation
Requires Python 3.10 or newer.
git clone https://github.com/Whytcard-Swiss-AI/wsai_fckdot.git
cd wsai_fckdot
python -m venv .venv
# Windows PowerShell: .venv\Scripts\Activate.ps1
# Linux/macOS: source .venv/bin/activate
python -m pip install -e .
python -m wsai_fckdot self-test
python -m wsai_fckdot setup-catalog
python -m wsai_fckdot setup-inventory C:\absolute\project --consent
python -m wsai_fckdot setup-plan C:\absolute\project setup.example.json --consent
# Review the plan_id, then:
python -m wsai_fckdot setup-apply C:\absolute\project setup.example.json PLAN_ID --consent
For development:
python -m pip install -e ".[dev]"
python -m pytest -q
MCP configuration
Use the virtual environment's absolute Python executable:
{
"mcpServers": {
"wsai_fckdot": {
"command": "/absolute/path/to/wsai_fckdot/.venv/bin/python",
"args": ["-m", "wsai_fckdot", "serve"],
"cwd": "/absolute/path/to/wsai_fckdot"
}
}
}
On Windows, command normally ends in .venv\\Scripts\\python.exe.
See MCP compatibility for protocol versions and wire behavior.
Safe workflow
First diagnose only the evidence already available:
{
"description": "The deploy hook is not found after enabling the plugin",
"problem_type": "hook",
"logs": ["ERROR hook deploy: not found"],
"config": {"hooks": [{"name": "deploy"}]},
"components": ["release-tools", "deploy"]
}
Then inspect the catalog or plan a narrow collection:
{
"control_ids": ["agents.hooks", "agents.plugins", "environment.path"],
"platform": "windows",
"execute": false
}
After the user explicitly approves those exact controls:
{
"control_ids": ["agents.hooks", "agents.plugins", "environment.path"],
"platform": "windows",
"execute": true,
"consent": true,
"include_output": false
}
Add the returned observations to a second diagnose call. A failed or unavailable probe becomes an explicit observation-incomplete finding.
CLI
python -m wsai_fckdot catalog
python -m wsai_fckdot coverage --platform windows
python -m wsai_fckdot collect agents.hooks agents.plugins --platform windows
python -m wsai_fckdot collect agents.hooks --platform windows --execute --consent
python -m wsai_fckdot diagnose problem.json --out reports
python -m wsai_fckdot self-test
The first collect command only produces a plan. The second explicitly executes one allowlisted probe and still omits output.
Agent skills
Three reusable public skills are included:
wsai_fckdot-installinstalls and verifies the MCP without collecting machine data;wsai_fckdot-useguides diagnosis, consent, narrow collection and post-fix verification;wsai_fckdot-setupguides setup inventory, conflict-safe consolidation, account profiles and approved application.
Source archives and wheels both include every skill's SKILL.md and agents/openai.yaml under the distribution's share/wsai_fckdot/skills data directory. Installing the Python package does not silently activate a skill in an agent client; copy or link the selected skill into that client's documented skill directory.
Extending wsai_fckdot
Controls live in wsai_fckdot.catalog; diagnostics live in wsai_fckdot.diagnostics. Every new control needs Windows, Linux and macOS probes, synthetic tests and an updated catalog version. Every new diagnostic needs a stable ID, evidence, explanation, safe fixes and positive/negative evaluation cases. See CONTRIBUTING.md.
Security
Read SECURITY.md before enabling output collection or setup application. Never share a report without reviewing it, because no generic redactor can guarantee removal of every private value from arbitrary third-party output.
License
MIT.
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