Mspbots logo

Mspbots

Organization
Servosity
mspbots

The first MSPbots tool anywhere - readable filters, alias-named resources, full exports, and the KPI history MSPbots itself doesn't keep. Trigger phrases: `pull the open tickets dataset from MSPbots`, `export MSPbots data to CSV`, `snapshot our MSPbots KPIs`, `is our ticket backlog up or down this week`, `what columns does this MSPbots dataset have`, `use mspbots`, `run mspbots-cli`.

Overview

PublisherServosity
Repositorymsp-skills
Skill namemspbots
Stars
68
Forks
14
Bundled files
96
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 96 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Servosity on GitHub. Read the source before you install it.

Installation

Install the Mspbots AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Servosity/msp-skills/tree/main/skills/mspbots
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Servosity/msp-skills.git /tmp/msp-skills
mkdir -p .claude/skills
cp -r /tmp/msp-skills/skills/mspbots .claude/skills/mspbots
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mspbots in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mspbots on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mspbots is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MSPbots - Claude Code Skill

Prerequisites: Install the CLI

This skill drives the mspbots-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:

  1. macOS / Linux:
    bash
    bash <(curl -fsSL https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/mspbots/install.sh)
  2. Windows (PowerShell):
    powershell
    iwr -useb https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/mspbots/install.ps1 | iex
  3. Verify: mspbots-cli --version
  4. Ensure ~/.local/bin (macOS / Linux) or %LOCALAPPDATA%\Programs\msp-skills (Windows) is on $PATH.

The installer downloads the mspbots-cli and mspbots-mcp binaries into ~/.local/bin (macOS / Linux) or %LOCALAPPDATA%\Programs\msp-skills (Windows). It does not register the skill with your agent and writes no MCP client config - see mcp-install.md for that wire-up.

If --version reports "command not found" after install, the runtime cannot see the binary directory on $PATH. Do not proceed with skill commands until verification succeeds.

MSPbots' Public API shares your BI datasets and widgets but ships with 19-digit IDs, a comma-encoded filter DSL, manual pagination, and no history. This CLI turns a shared API key into a usable data faucet: register aliases once, filter with readable predicates, export whole tables in one command, and snapshot KPIs into local SQLite for diffs and trends no MSPbots surface can show.

When to Use This CLI

Reach for this CLI whenever MSP business-intelligence data living in MSPbots needs to leave the dashboard: piping ticket/SLA/utilization rows into scripts, capturing scheduled KPI snapshots for week-over-week reporting, exporting full datasets to CSV for finance, or letting an AI agent answer service-desk questions from real data. It is the only programmatic MSPbots surface that exists.

Anti-triggers

Do not use this CLI for:

  • Creating, rotating, or binding MSPbots API keys - that is UI-only (Settings → Public API)
  • Managing bots, dashboards, alerts, or any write operation inside MSPbots - the Public API is strictly read-only
  • Pulling PSA/RMM data that is not bound to your key - bind it in MSPbots first, or use that tool's own API
  • Reading widgets built with measure or calculate layers - the Public API does not support them

Unique Capabilities

These capabilities aren't available in any other tool for this API.

Local state that compounds

  • registry - Name your bound datasets and widgets once, then use readable aliases everywhere instead of 19-digit resource IDs.

    Agents and scripts can address resources by stable, human-readable names instead of copy-pasted snowflake IDs.

    bash
    mspbots-cli registry add <alias> <resourceId> --type dataset
  • snapshot - Capture point-in-time copies of any dataset or widget into local SQLite - the history MSPbots doesn't keep.

    Run it on a schedule and every later question about "how has this changed" becomes answerable offline.

    bash
    mspbots-cli snapshot <alias>
  • trend - Time-series and point-over-point deltas for any numeric column across stored snapshots.

    Answers "is this KPI up or down since last week" - the question the live API structurally cannot answer.

    bash
    mspbots-cli trend <alias> --column "Open Count"
  • diff - Row-level added/removed/changed comparison between two stored snapshots of the same resource.

    Shows exactly which tickets entered or left a queue between two captures, not just the count.

    bash
    mspbots-cli diff <alias>

Agent-native plumbing

  • pull - Write filters like "Update Date >= 2026-05-29" and the CLI compiles them into MSPbots' comma-encoded operator DSL.

    Reach for this instead of hand-building query strings; it handles operator encoding, spaces in column names, and URL-escaping.

    bash
    mspbots-cli pull <alias> --where "Update Date >= 2026-05-29" --where "Status = Open" --json
  • export - Dump an entire dataset or widget to CSV or JSONL, walking every page automatically.

    One command replaces a babysat pagination loop when feeding spreadsheets or downstream pipelines.

    bash
    mspbots-cli export <alias> --format csv
  • describe - Sample live rows and infer the column names and types of a dataset or widget.

    Run it before building --where filters so column names and types are known instead of guessed.

    bash
    mspbots-cli describe <alias>

Command Reference

dataset - Fetch rows of datasets bound to your Public API key

  • mspbots-cli dataset <resourceId> - Fetch one page of rows from a dataset bound to your API key

widget - Fetch data of widgets bound to your Public API key

  • mspbots-cli widget <resourceId> - Fetch one page of data from a bound widget (widgets with measure or calculate layers are not supported by the Public

Finding the right command

When you know what you want to do but not which command does it, ask the CLI directly:

bash
mspbots-cli which "<capability in your own words>"

which resolves a natural-language capability query to the best matching command from this CLI's curated feature index. Exit code 0 means at least one match; exit code 2 means no confident match - fall back to --help or use a narrower query.

Recipes

Register and pull a shared dataset

bash
mspbots-cli registry add <alias> <resourceId> --type dataset

One-time alias setup; every later command addresses the resource by its alias.

Filtered pull with readable predicates

bash
mspbots-cli pull <alias> --where "Update Date >= 2026-05-01" --where "Status = Open" --json

The CLI compiles readable operators into MSPbots' comma-encoded query DSL and URL-encodes spaced column names.

Agent-shaped KPI read

bash
mspbots-cli pull <alias> --agent --select row_count,rows

Returns only the row count and rows fields in agent-envelope JSON - bounded context for LLM consumption.

Full CSV export for finance

bash
mspbots-cli export <alias> --format csv

Walks every page via current/size automatically and streams one clean CSV.

Week-over-week KPI movement

bash
mspbots-cli trend <alias> --column "Open Count"

Aggregates the column across stored snapshots; pair with a scheduled snapshot to keep the series growing.

Auth Setup

MSPbots uses a raw API key sent as an apikey request header. An MSPbots admin creates the key in the MSPbots app under Settings → Public API (Add New Key, type Custom), flips the global Enable Public API toggle ON, and explicitly binds each dataset and widget the key may read. Set the key in your environment as MSPBOTS_API_KEY. Every endpoint is read-only; a key can never write anything. If a pull returns "resource unbound", the dataset or widget has not been bound to your key - that binding happens in the MSPbots UI, not in this CLI.

Run mspbots-cli doctor to verify setup.

Agent Mode

Add --agent to any command. Expands to: --json --compact --no-input --no-color --yes.

  • Pipeable - JSON on stdout, errors on stderr

  • Filterable - --select keeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:

    bash
    mspbots-cli dataset <id> --agent --select id,name,status
  • Previewable - --dry-run shows the request without sending

  • Offline-friendly - sync/search commands can use the local SQLite store when available

  • Non-interactive - never prompts, every input is a flag

  • Read-only - do not use this CLI for create, update, delete, publish, comment, upvote, invite, order, send, or other mutating requests

Response envelope

Commands that read from the local store or the API wrap output in a provenance envelope:

json
{
  "meta": {"source": "live" | "local", "synced_at": "...", "reason": "..."},
  "results": <data>
}

Parse .results for data and .meta.source to know whether it's live or local. A human-readable N results (live) summary is printed to stderr only when stdout is a terminal AND no machine-format flag (--json, --csv, --compact, --quiet, --plain, --select) is set - piped/agent consumers and explicit-format runs get pure JSON on stdout.

Agent Feedback

When you (or the agent) notice something off about this CLI, record it:

mspbots-cli feedback "the --since flag is inclusive but docs say exclusive"
mspbots-cli feedback --stdin < notes.txt
mspbots-cli feedback list --json --limit 10

Entries are stored locally at ~/.local/share/mspbots-cli/feedback.jsonl. They are never POSTed unless MSPBOTS_FEEDBACK_ENDPOINT is set AND either --send is passed or MSPBOTS_FEEDBACK_AUTO_SEND=true. Default behavior is local-only.

Write what surprised you, not a bug report. Short, specific, one line: that is the part that compounds.

Output Delivery

Every command accepts --deliver <sink>. The output goes to the named sink in addition to (or instead of) stdout, so agents can route command results without hand-piping. Three sinks are supported:

SinkEffect
stdoutDefault; write to stdout only
file:<path>Atomically write output to <path> (tmp + rename)
webhook:<url>POST the output body to the URL (application/json or application/x-ndjson when --compact)

Unknown schemes are refused with a structured error naming the supported set. Webhook failures return non-zero and log the URL + HTTP status on stderr.

Named Profiles

A profile is a saved set of flag values, reused across invocations. Use it when a scheduled agent calls the same command every run with the same configuration - HeyGen's "Beacon" pattern.

mspbots-cli profile save briefing --json
mspbots-cli --profile briefing dataset <id>
mspbots-cli profile list --json
mspbots-cli profile show briefing
mspbots-cli profile delete briefing --yes

Explicit flags always win over profile values; profile values win over defaults. agent-context lists all available profiles under available_profiles so introspecting agents discover them at runtime.

Exit Codes

CodeMeaning
0Success
2Usage error (wrong arguments)
3Resource not found
4Authentication required
5API error (upstream issue)
7Rate limited (wait and retry)
10Config error

Argument Parsing

Parse $ARGUMENTS:

  1. Empty, help, or --help → show mspbots-cli --help output
  2. Starts with install → ends with mcp → MCP installation; otherwise → see Prerequisites above
  3. Anything else → Direct Use (execute as CLI command with --agent)

MCP Server Installation

  1. Install the MCP binary (run the install script from the Prerequisites section, or see mcp-install.md for per-agent wire-up).
  2. Register with Claude Code:
    bash
    claude mcp add mspbots-mcp -- mspbots-mcp
  3. Verify: claude mcp list

Direct Use

  1. Check if installed: which mspbots-cli If not found, offer to install (see Prerequisites at the top of this skill).
  2. Match the user query to the best command from the Unique Capabilities and Command Reference above.
  3. Execute with the --agent flag:
    bash
    mspbots-cli <command> [subcommand] [args] --agent
  4. If ambiguous, drill into subcommand help: mspbots-cli <command> --help.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 36 more files.

Frequently asked questions

What does the Mspbots AI skill do?

The first MSPbots tool anywhere - readable filters, alias-named resources, full exports, and the KPI history MSPbots itself doesn't keep. Trigger phrases: `pull the open tickets dataset from MSPbots`, `export MSPbots data to CSV`, `snapshot our MSPbots KPIs`, `is our ticket backlog up or down this week`, `what columns does this MSPbots dataset have`, `use mspbots`, `run mspbots-cli`.

Why use Mspbots on TypingMind?

Because you install it once and use it with any model. Mspbots is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mspbots in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Servosity/msp-skills/tree/main/skills/mspbots. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mspbots?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mspbots?

As many as you like. As long as a model supports skills, you can use Mspbots with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mspbots AI skill free?

Yes. It is published on GitHub by Servosity under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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