agent-tool-store 2.0.1

Universal tool platform for AI agents — 14+ toolsets, MCP, YAML workflows, provider adapters (OpenAI/Anthropic/LangChain)

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title: AgentToolStore Registry emoji: 🛠️ colorFrom: blue colorTo: purple sdk: docker app_port: 7860 pinned: false

AgentToolStore

A package index for agent tools. PyPI for Python packages, npm for JavaScript — ToolStore does the same for agent-callable toolsets. Agents discover tools through a single tool_store function instead of wiring up dozens of tools by hand.

→ Client SDK docs — installing, integrating into agents, CLI, MCP bridge, skills → Registry server docs — API endpoints, running locally, deploying on HF Spaces

Live registry: mrw33554432-agenttoolstore.hf.space

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How it works

toolstore update                     ← downloads index.json from registry
       │
       ▼
┌─────────────────────────┐
│  Local index cache       │  ← search and info read from here (no network)
└─────────────────────────┘
       │
       ▼
┌─────────────────────────┐
│  tool_store(execute)     │  ← fetches code from registry on demand
│  → temp dir → import     │     runs in-process, no Docker
│  → call function → JSON  │
└─────────────────────────┘

1. toolstore update pulls the registry index and caches it locally
2. search / info read from the local cache — instant, no network
3. execute fetches code from the registry, installs deps explicitly, runs in-process, returns JSON

---

Installation

pip install toolstore

Or from source:

git clone https://github.com/Mrw33554432/AgentToolStore.git
cd AgentToolStore/client
pip install -e .

Requirements: Python ≥3.10, httpx, pydantic, rich, typer.

---

Adding to Your Agent

Add one tool definition and one handler. The agent discovers every published toolset through a single tool_store call.

How it fits into an agent loop

System prompt                         Tool call loop
─────────────────────────────────     ─────────────────────────────────
"Tool store includes but not          1. Agent calls tool_store(search)
 limited to: Echo Service,                → discovers xlsx-toolkit
 calculator, weather, ..."
                                      2. Agent calls tool_store(info)
                                         → gets xlsx_read params + docs

                                      3. Agent calls tool_store(execute)
                                         → runs xlsx_read, gets result

                                      4. Agent calls tool_store(close)
                                         → frees context space

1. Tool definition

Register this in your agent's function-calling tool list:

TOOL_STORE_SCHEMA = {
    "type": "function",
    "function": {
        "name": "tool_store",
        "description": (
            "A universal tool manager that lets you search, inspect, "
            "and execute thousands of tools and local utilities."
        ),
        "parameters": {
            "type": "object",
            "properties": {
                "action": {
                    "type": "string",
                    "enum": ["search", "execute", "info", "close"],
                    "description": (
                        "The action to perform: 'search' finds tools "
                        "matching a query; 'execute' runs a tool; "
                        "'info' adds a tool to your context so you can "
                        "see its parameters; 'close' removes it."
                    ),
                },
                "query": {
                    "type": "string",
                    "description": "Search query string (for action='search')",
                },
                "tool_name": {
                    "type": "string",
                    "description": (
                        "Name of the tool to inspect, execute, or close "
                        "(required for action='info', 'execute', or 'close')"
                    ),
                },
                "arguments": {
                    "type": "object",
                    "description": (
                        "Arguments for the tool execution "
                        "(required for action='execute')"
                    ),
                },
            },
            "required": ["action"],
        },
    },
}

2. Handler

Wire the native function into your tool-call router. The native function handles search, info, and execute — add a small shim for close:

from toolstore.native_tool import tool_store_tool

def handle_tool_store(action: str, **kwargs) -> str:
    if action == "close":
        return f"Closed tool '{kwargs.get('tool_name', '')}'."
    return tool_store_tool(action=action, **kwargs)

3. Secondary tools prompt

Most tools are exposure: secondary — too many to list in every system message. Inject a compact listing into the system prompt instead. Call get_secondary_tool_names() then info with format="secondary":

from toolstore.native_tool import get_secondary_tool_names, tool_store_tool

names = get_secondary_tool_names()
listing = tool_store_tool(action="info", tool_names=names, format="secondary")
system_prompt += f"\n\n{listing}"

Produces:

Tool store includes but is not limited to the following tools:
- Echo Service
- calculator
- weather
- skill:algorithmic-art
...

The agent sees names; when it needs a tool it calls info again (without format="secondary") for the full schema, then execute.

4. Agent conversation example

Agent: tool_store(action="search", query="read Excel files")
  → Found: xlsx-toolkit — Read, create, and manipulate Excel files

Agent: tool_store(action="info", tool_name="xlsx-toolkit")
  → Returns bindings for xlsx_read, xlsx_sheets, xlsx_to_csv, xlsx_create
    with parameter types and docstrings for each

Agent: tool_store(action="execute", tool_name="xlsx-toolkit",
                  arguments={"function": "xlsx_read",
                             "filepath": "/workspace/report.xlsx"})
  → {"sheets": ["Sheet1"], "data": {"Sheet1": [[...], ...]}}

Agent: tool_store(action="close", tool_name="xlsx-toolkit")
  → Closed tool 'xlsx-toolkit'.

5. Execution model

Property	Behaviour
Runtime	In-process — no Docker, no sandbox
Code origin	Fetched from registry, cached after first download
Dependencies	Never auto-installed; agent gets a clear error listing what's needed
Isolation	Each toolset runs in its own temp directory
Safety	All code is visible in the registry; deps are explicit; agent decides what to install

6. Local execution (no registry)

Skip the registry entirely and call toolsets from a local directory:

from toolstore.exec_tools import _execute_toolset_local

result = _execute_toolset_local(
    toolset_path="./toolsets/xlsx-toolkit",
    function_name="xlsx_read",
    filepath="/workspace/data.xlsx",
)

---

CLI Usage

# Pull the latest index from the registry
toolstore update

# Search for tools
toolstore search "spreadsheet"

# Inspect a toolset
toolstore info xlsx-toolkit

# Execute a function
toolstore use text-transform --function text_stats text="Hello world."

# Publish your own toolset
toolstore login --username <user> --password <pass>
toolstore toolset publish ./toolsets/my-toolkit

# Delete a toolset
toolstore delete my-toolkit

# Run ToolStore as an MCP server (stdio or SSE)
toolstore serve

# Export the tool_store schema for use with OpenAI / vLLM
toolstore export

# Manage skills
toolstore skill discover /path/to/skills
toolstore skill list-dirs

Full command reference:

Command	Description
update	Pull the latest registry index and scan local MCP servers
search	Search for tools by name, description, or tags
use	Execute a tool function immediately
info	Show detailed schema and documentation for a tool
login	Authenticate with the registry to publish
publish	Publish a new tool or update an existing one
delete	Remove a tool from the registry
export	Export the meta-tool schema (OpenAI / vLLM formats)
serve	Run ToolStore as an MCP server (stdio or SSE)
skill	Manage Agent Skills (scan, discover, publish, …)
toolset	Manage toolsets (scan, list, publish, …)
mcp-server	Register and manage MCP servers
docker	Configure Docker execution permissions

---

Writing a Toolset

A toolset is a directory with two files:

my-toolkit/
├── toolset.py    # @tool functions (code bindings)
└── doc.md        # human + agent guidance

toolset.py

Every function decorated with @tool becomes a callable binding. The decorator auto-generates an OpenAI function-calling schema from type hints and docstrings:

from toolstore.toolset import tool

@tool
def my_function(*, input: str, count: int = 1) -> dict:
    """Do something useful.

    Args:
        input: The input text.
        count: How many times to repeat.
    """
    return {"result": input * count}

Rules:

• Use keyword-only arguments (*,)
• Annotate every parameter with a type hint
• Write a Google-style docstring with an Args: section
• Return a JSON-serializable dict

Two kinds of toolsets

Type	toolset.py	doc.md	Example
Code	Real @tool functions	Full docs	xlsx-toolkit, file-verify
Doc-only	Minimal empty module	Full guidance	stuck-toolkit

Doc-only toolsets are valid — they carry skill content without code bindings. No placeholder functions allowed. Code or nothing.

---

Registry API

The registry is a FastAPI server backed by SQLite, hosted on Hugging Face Spaces. All endpoints are public except auth and publish.

Endpoint	Method	Auth	Description
/	GET	No	Browse page (HTML) — dark-themed cards showing all published toolsets
/api	GET	No	API root
/health	GET	No	Health check — database connectivity status
/index.json	GET	No	Full index — every toolset with metadata, bindings, and full source code
/auth/register	POST	No	Register a new user account
/auth/token	POST	No	Login — returns JWT access token (OAuth2 password flow)
/publish	POST	JWT	Publish a new toolset or update an existing one
/tools/{name}	DELETE	JWT	Delete a toolset

Running your own registry

cd server
pip install -r requirements.txt
python init_db.py          # create SQLite database
uvicorn app.main:app --port 8000

Set TOOLSTORE_REGISTRY_URL=http://localhost:8000/index.json to point the CLI at a local registry. The default is:

https://mrw33554432-agenttoolstore.hf.space/index.json

---

Toolsets Catalog

All 14 toolsets published on the live registry.

Document processing

Toolset	Functions	Dependencies
xlsx-toolkit	xlsx_read · xlsx_sheets · xlsx_to_csv · xlsx_create	openpyxl
pdf-toolkit	pdf_extract · pdf_meta · pdf_merge · pdf_form_fields	pdfplumber, PyPDF2
docx-toolkit	docx_read · docx_info · docx_extract_tables · docx_create	python-docx
pptx-toolkit	pptx_read · pptx_info · pptx_create	python-pptx

Utility

Toolset	Functions	Dependencies
text-transform	text_diff · regex_extract · markdown_table · text_stats	stdlib
file-verify	check_json · check_yaml · check_csv · file_hash · detect_encoding	PyYAML, chardet (optional)
calc-toolkit	eval_expression · convert_unit · basic_stats	stdlib
text-gen	lorem_words · lorem_paragraphs · generate_sentences · generate_data	stdlib
batch-ops	batch_rename · batch_find_replace · batch_stats · batch_copy	stdlib

Guidance & diagnostics

Toolset	Functions	Dependencies
debug-toolkit	analyze_error · extract_log_patterns	stdlib
webapp-testing-toolkit	check_url · extract_urls	stdlib
doc-coauthoring-toolkit	document_outline · markdown_template	stdlib
internal-comms-toolkit	comms_template · format_bullets	stdlib
stuck-toolkit	doc-only — no code bindings	—

---

Project Structure

AgentToolStore/
├── client/                          # Python SDK (pip install toolstore)
│   ├── pyproject.toml
│   └── src/toolstore/
│       ├── cli.py                   # Typer CLI (update, search, use, publish, …)
│       ├── native_tool.py           # tool_store_tool() — the agent-facing entry point
│       ├── toolset.py               # @tool decorator + schema generation
│       ├── toolset_manager.py       # AST-based toolset discovery & publishing
│       ├── exec_tools.py            # Local + remote toolset execution
│       ├── config_manager.py        # Settings, registry URL, env-var overrides
│       ├── mcp_client.py            # MCP client (stdio / SSE transport)
│       ├── mcp_server.py            # MCP server — expose ToolStore via MCP
│       ├── index_manager.py         # Local index cache
│       ├── transport.py             # stdio / SSE / streamable-http transports
│       ├── skill_manager.py         # Agent Skills loader + discovery
│       ├── skill_discovery.py       # Skill directory scanner
│       ├── schema_converter.py      # Convert ToolStore schemas to OpenAI format
│       ├── management/              # Management server + SPA (custom HTTP server)
│       │   ├── server.py
│       │   ├── api_helpers.py
│       │   ├── api_mcp.py
│       │   ├── api_skills.py
│       │   └── static/
│       │       └── app.js
│       └── docker_pool.py           # Docker container pool (optional)
│
├── server/                          # Registry server (FastAPI + SQLite)
│   ├── Dockerfile                   # HF Spaces deployment
│   ├── requirements.txt
│   ├── init_db.py
│   └── app/
│       ├── main.py                  # FastAPI app — browse page, API, auth
│       ├── models.py                # Pydantic models (ToolSet, Binding, …)
│       ├── database.py              # SQLite with HF Storage Bucket
│       ├── db.py                    # Connection helper
│       └── auth.py                  # JWT auth + user management
│
├── toolsets/                        # All 14 published toolsets
│   ├── xlsx-toolkit/
│   ├── pdf-toolkit/
│   ├── docx-toolkit/
│   ├── pptx-toolkit/
│   ├── text-transform/
│   ├── file-verify/
│   ├── calc-toolkit/
│   ├── text-gen/
│   ├── batch-ops/
│   ├── debug-toolkit/
│   ├── webapp-testing-toolkit/
│   ├── doc-coauthoring-toolkit/
│   ├── internal-comms-toolkit/
│   └── stuck-toolkit/
│
├── Dockerfile                       # Root Dockerfile (HF Spaces entry point)
├── _publish_toolsets.py             # Utility: batch-publish all toolsets
├── LICENSE                          # MIT
└── README.md

---

Development

git clone https://github.com/Mrw33554432/AgentToolStore.git
cd AgentToolStore
pip install -e client/

# Run a local registry for testing
cd server && pip install -r requirements.txt && python init_db.py
uvicorn app.main:app --port 8000 &

# Point the CLI at your local registry
export TOOLSTORE_REGISTRY_URL=http://localhost:8000/index.json

# Test a toolset
toolstore use text-transform --function text_stats text="Hello world."

---

Contributing

1. Write a toolset (toolsets/<name>/toolset.py + doc.md)
2. Decorate every callable function with @tool
3. Use keyword-only arguments with type hints and Google-style docstrings
4. Keep imports inside each function so they fail cleanly at call time
5. Test with toolstore use <name> --function <fn> <args>
6. Open a PR against main

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Remaining Work

• xlsx / pdf / docx / pptx testing — these toolsets need openpyxl, pdfplumber, python-docx, and python-pptx installed in the test environment for full integration tests
• Rate limiting — the registry server has no rate limiting on public endpoints
• Large payload handling — docx/pptx toolset bindings can be large; better error handling for oversized publishes

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License

MIT — see LICENSE