mirror of
https://github.com/NousResearch/hermes-agent.git
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Extends the Windows-gating work to the optional-skills/ tree. Every
SKILL.md that previously omitted the platforms: field now carries an
explicit declaration, which Hermes's loader (agent.skill_utils.
skill_matches_platform) honors to skip-load on incompatible OSes.
58 skills declared cross-platform (platforms: [linux, macos, windows]):
autonomous-ai-agents/blackbox, autonomous-ai-agents/honcho
blockchain/base, blockchain/solana
communication/one-three-one-rule
creative/blender-mcp, creative/concept-diagrams, creative/hyperframes,
creative/kanban-video-orchestrator, creative/meme-generation
devops/cli (inference-sh-cli), devops/docker-management
dogfood/adversarial-ux-test
email/agentmail
finance/3-statement-model, finance/comps-analysis, finance/dcf-model,
finance/excel-author, finance/lbo-model, finance/merger-model,
finance/pptx-author
health/fitness-nutrition, health/neuroskill-bci
mcp/fastmcp, mcp/mcporter
migration/openclaw-migration
mlops/accelerate, mlops/chroma, mlops/clip, mlops/guidance,
mlops/hermes-atropos-environments, mlops/huggingface-tokenizers,
mlops/instructor, mlops/lambda-labs, mlops/llava, mlops/modal,
mlops/peft, mlops/pinecone, mlops/pytorch-lightning, mlops/qdrant,
mlops/saelens, mlops/simpo, mlops/stable-diffusion
productivity/canvas, productivity/shop-app, productivity/shopify,
productivity/siyuan, productivity/telephony
research/domain-intel, research/drug-discovery, research/duckduckgo-search,
research/gitnexus-explorer, research/parallel-cli, research/scrapling
security/1password, security/oss-forensics, security/sherlock
web-development/page-agent
5 skills gated from Windows (platforms: [linux, macos]):
mlops/flash-attention - Flash Attention wheels are Linux-first; Windows
install requires building from source with CUDA
mlops/faiss - faiss-gpu has no Windows wheel; gate rather than
leak partial (faiss-cpu) support
mlops/nemo-curator - NVIDIA NeMo ecosystem has no first-class Windows path
mlops/slime - Megatron+SGLang RL stack is Linux-only in practice
mlops/whisper - openai-whisper + ffmpeg setup on Windows is
non-trivial; gate until Windows install stanza lands
Methodology: scanned every SKILL.md for Windows-hostile signals
(apt-get, brew, systemd, osascript, ptrace, X11 binaries, POSIX-only
Python APIs, Docker POSIX $(pwd) bind-mounts, explicit 'linux-only' /
'macos-only' text). 3 skills flagged as having hard signals on review:
docker-management and qdrant only had POSIX $(pwd) docker examples and
the tools themselves (Docker Desktop, Qdrant) run fine on Windows —
declared ALL. whisper had an apt/brew ffmpeg install path and nothing
else but the openai-whisper Windows install story is rough enough to
warrant gating.
Strict-over-lenient policy: when in doubt, gate. Easier to un-gate after
verified Windows support lands than to leak partial support that
manifests as mid-task failures for Windows users.
300 lines
8.2 KiB
Markdown
300 lines
8.2 KiB
Markdown
---
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name: fastmcp
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description: Build, test, inspect, install, and deploy MCP servers with FastMCP in Python. Use when creating a new MCP server, wrapping an API or database as MCP tools, exposing resources or prompts, or preparing a FastMCP server for Claude Code, Cursor, or HTTP deployment.
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version: 1.0.0
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author: Hermes Agent
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license: MIT
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platforms: [linux, macos, windows]
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metadata:
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hermes:
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tags: [MCP, FastMCP, Python, Tools, Resources, Prompts, Deployment]
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homepage: https://gofastmcp.com
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related_skills: [native-mcp, mcporter]
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prerequisites:
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commands: [python3]
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---
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# FastMCP
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Build MCP servers in Python with FastMCP, validate them locally, install them into MCP clients, and deploy them as HTTP endpoints.
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## When to Use
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Use this skill when the task is to:
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- create a new MCP server in Python
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- wrap an API, database, CLI, or file-processing workflow as MCP tools
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- expose resources or prompts in addition to tools
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- smoke-test a server with the FastMCP CLI before wiring it into Hermes or another client
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- install a server into Claude Code, Claude Desktop, Cursor, or a similar MCP client
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- prepare a FastMCP server repo for HTTP deployment
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Use `native-mcp` when the server already exists and only needs to be connected to Hermes. Use `mcporter` when the goal is ad-hoc CLI access to an existing MCP server instead of building one.
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## Prerequisites
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Install FastMCP in the working environment first:
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```bash
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pip install fastmcp
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fastmcp version
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```
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For the API template, install `httpx` if it is not already present:
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```bash
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pip install httpx
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```
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## Included Files
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### Templates
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- `templates/api_wrapper.py` - REST API wrapper with auth header support
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- `templates/database_server.py` - read-only SQLite query server
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- `templates/file_processor.py` - text-file inspection and search server
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### Scripts
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- `scripts/scaffold_fastmcp.py` - copy a starter template and replace the server name placeholder
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### References
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- `references/fastmcp-cli.md` - FastMCP CLI workflow, installation targets, and deployment checks
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## Workflow
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### 1. Pick the Smallest Viable Server Shape
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Choose the narrowest useful surface area first:
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- API wrapper: start with 1-3 high-value endpoints, not the whole API
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- database server: expose read-only introspection and a constrained query path
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- file processor: expose deterministic operations with explicit path arguments
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- prompts/resources: add only when the client needs reusable prompt templates or discoverable documents
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Prefer a thin server with good names, docstrings, and schemas over a large server with vague tools.
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### 2. Scaffold from a Template
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Copy a template directly or use the scaffold helper:
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```bash
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python ~/.hermes/skills/mcp/fastmcp/scripts/scaffold_fastmcp.py \
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--template api_wrapper \
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--name "Acme API" \
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--output ./acme_server.py
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```
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Available templates:
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```bash
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python ~/.hermes/skills/mcp/fastmcp/scripts/scaffold_fastmcp.py --list
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```
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If copying manually, replace `__SERVER_NAME__` with a real server name.
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### 3. Implement Tools First
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Start with `@mcp.tool` functions before adding resources or prompts.
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Rules for tool design:
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- Give every tool a concrete verb-based name
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- Write docstrings as user-facing tool descriptions
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- Keep parameters explicit and typed
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- Return structured JSON-safe data where possible
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- Validate unsafe inputs early
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- Prefer read-only behavior by default for first versions
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Good tool examples:
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- `get_customer`
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- `search_tickets`
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- `describe_table`
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- `summarize_text_file`
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Weak tool examples:
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- `run`
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- `process`
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- `do_thing`
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### 4. Add Resources and Prompts Only When They Help
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Add `@mcp.resource` when the client benefits from fetching stable read-only content such as schemas, policy docs, or generated reports.
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Add `@mcp.prompt` when the server should provide a reusable prompt template for a known workflow.
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Do not turn every document into a prompt. Prefer:
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- tools for actions
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- resources for data/document retrieval
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- prompts for reusable LLM instructions
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### 5. Test the Server Before Integrating It Anywhere
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Use the FastMCP CLI for local validation:
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```bash
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fastmcp inspect acme_server.py:mcp
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fastmcp list acme_server.py --json
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fastmcp call acme_server.py search_resources query=router limit=5 --json
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```
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For fast iterative debugging, run the server locally:
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```bash
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fastmcp run acme_server.py:mcp
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```
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To test HTTP transport locally:
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```bash
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fastmcp run acme_server.py:mcp --transport http --host 127.0.0.1 --port 8000
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fastmcp list http://127.0.0.1:8000/mcp --json
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fastmcp call http://127.0.0.1:8000/mcp search_resources query=router --json
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```
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Always run at least one real `fastmcp call` against each new tool before claiming the server works.
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### 6. Install into a Client When Local Validation Passes
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FastMCP can register the server with supported MCP clients:
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```bash
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fastmcp install claude-code acme_server.py
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fastmcp install claude-desktop acme_server.py
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fastmcp install cursor acme_server.py -e .
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```
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Use `fastmcp discover` to inspect named MCP servers already configured on the machine.
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When the goal is Hermes integration, either:
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- configure the server in `~/.hermes/config.yaml` using the `native-mcp` skill, or
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- keep using FastMCP CLI commands during development until the interface stabilizes
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### 7. Deploy After the Local Contract Is Stable
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For managed hosting, Prefect Horizon is the path FastMCP documents most directly. Before deployment:
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```bash
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fastmcp inspect acme_server.py:mcp
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```
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Make sure the repo contains:
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- a Python file with the FastMCP server object
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- `requirements.txt` or `pyproject.toml`
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- any environment-variable documentation needed for deployment
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For generic HTTP hosting, validate the HTTP transport locally first, then deploy on any Python-compatible platform that can expose the server port.
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## Common Patterns
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### API Wrapper Pattern
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Use when exposing a REST or HTTP API as MCP tools.
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Recommended first slice:
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- one read path
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- one list/search path
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- optional health check
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Implementation notes:
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- keep auth in environment variables, not hardcoded
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- centralize request logic in one helper
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- surface API errors with concise context
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- normalize inconsistent upstream payloads before returning them
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Start from `templates/api_wrapper.py`.
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### Database Pattern
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Use when exposing safe query and inspection capabilities.
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Recommended first slice:
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- `list_tables`
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- `describe_table`
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- one constrained read query tool
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Implementation notes:
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- default to read-only DB access
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- reject non-`SELECT` SQL in early versions
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- limit row counts
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- return rows plus column names
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Start from `templates/database_server.py`.
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### File Processor Pattern
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Use when the server needs to inspect or transform files on demand.
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Recommended first slice:
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- summarize file contents
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- search within files
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- extract deterministic metadata
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Implementation notes:
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- accept explicit file paths
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- check for missing files and encoding failures
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- cap previews and result counts
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- avoid shelling out unless a specific external tool is required
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Start from `templates/file_processor.py`.
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## Quality Bar
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Before handing off a FastMCP server, verify all of the following:
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- server imports cleanly
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- `fastmcp inspect <file.py:mcp>` succeeds
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- `fastmcp list <server spec> --json` succeeds
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- every new tool has at least one real `fastmcp call`
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- environment variables are documented
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- the tool surface is small enough to understand without guesswork
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## Troubleshooting
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### FastMCP command missing
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Install the package in the active environment:
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```bash
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pip install fastmcp
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fastmcp version
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```
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### `fastmcp inspect` fails
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Check that:
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- the file imports without side effects that crash
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- the FastMCP instance is named correctly in `<file.py:object>`
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- optional dependencies from the template are installed
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### Tool works in Python but not through CLI
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Run:
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```bash
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fastmcp list server.py --json
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fastmcp call server.py your_tool_name --json
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```
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This usually exposes naming mismatches, missing required arguments, or non-serializable return values.
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### Hermes cannot see the deployed server
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The server-building part may be correct while the Hermes config is not. Load the `native-mcp` skill and configure the server in `~/.hermes/config.yaml`, then restart Hermes.
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## References
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For CLI details, install targets, and deployment checks, read `references/fastmcp-cli.md`.
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