claude mcp add ingestion-mcp -- uvx ingestion-mcp{
"mcpServers": {
"ingestion-mcp": {
"command": "uvx",
"args": ["ingestion-mcp"]
}
}
}Resumen de MCP Servers
# ingestion-mcp
A small, read-only [Model Context Protocol](https://modelcontextprotocol.io) server that lets an
AI host (e.g. Claude Code) answer questions about your **Kenda** token spend and waste straight
from the terminal — _"how much did I spend this week?"_, _"which agent is wasting the most?"_.
It is a **query surface only**: it never captures or writes usage. It reads the token-authed
`/collector/*` endpoints of the Kenda API using the endpoint + token from `~/.kenda/config.json`
(the same ingest token the Kenda collector writes), which resolve the token to its org
server-side — so the terminal needs no browser/Auth0 session.
<!-- mcp-name: io.github.kenda-co/ingestion-mcp -->
## Tools
| Tool | Endpoint | Returns |
|------|----------|---------|
| `kenda_spend_summary` | `GET /collector/summary` | Top-line spend, waste, and health for your org |
| `kenda_waste_by_agent` | `GET /collector/agents` | Per-agent spend and redundant (wasted) dollars |
## Install
```sh
uv tool install ingestion-mcp # or: pipx install ingestion-mcp
```
The console script `kenda-mcp` runs the stdio server. `uvx ingestion-mcp` runs it without
installing anything.
`uv` and `pipx` are recommended over a bare `pip install` because this ships a command-line
entry point, and `pip` refuses to install into a Homebrew or distro-managed interpreter at all
(`error: externally-managed-environment`, PEP 668). If you only have `pip`, use
`pip install --user ingestion-mcp`. Both `uv` and `pipx` install into `~/.local/bin`, which is
not on `PATH` by default on macOS — if `kenda-mcp` is not found afterwards, that is why.
## Configure
The server reads `~/.kenda/config.json`:
```json
{
"endpoint": "https://api.kenda.app",
"token": "kenda_your-ingest-token"
}
```
Only `endpoint` and `token` are required for queries. Both are written for you by
`kenda-collect init` (the Kenda collector) or the Claude Code plugin's `/kenda-setup`. Environment
variables override the file (`KENDA_ENDPOINT`, `KENDA_TOKEN`) for CI and power users.
## Use with your AI host
The server is plain stdio MCP: every host below runs the same one-line command, `kenda-mcp` —
only the config file differs. After registering, ask your assistant: _"what did I spend this
week?"_ or _"which agent is wasting the most?"_.
### Claude Code
`.mcp.json` in the project (or `claude mcp add kenda -- kenda-mcp`):
```json
{
"mcpServers": {
"kenda": { "command": "kenda-mcp" }
}
}
```
### Cursor
`~/.cursor/mcp.json` (all projects) or `.cursor/mcp.json` (one project):
```json
{
"mcpServers": {
"kenda": { "command": "kenda-mcp" }
}
}
```
### Windsurf
`~/.codeium/windsurf/mcp_config.json` ([docs](https://docs.devin.ai/desktop/cascade/mcp)):
```json
{
"mcpServers": {
"kenda": { "command": "kenda-mcp" }
}
}
```
### VS Code (Copilot agent mode)
`.vscode/mcp.json` for one workspace — or run **MCP: Open User Configuration** from the
command palette to register it for all workspaces. Note the key is `servers` here, not
`mcpServers`:
```json
{
"servers": {
"kenda": { "type": "stdio", "command": "kenda-mcp" }
}
}
```
### Codex CLI
`~/.codex/config.toml` (or `codex mcp add kenda -- kenda-mcp`):
```toml
[mcp_servers.kenda]
command = "kenda-mcp"
```
### Gemini CLI
`~/.gemini/settings.json` (or `.gemini/settings.json` in a project):
```json
{
"mcpServers": {
"kenda": { "command": "kenda-mcp" }
}
}
```
### Troubleshooting
If your host reports the server as failed, run the built-in self-test — it works even when
the `mcp` package is broken, and tells you whether the problem is your config, the network,
or the host:
```sh
kenda-mcp --check
```
It prints the version, the config it resolved (token masked), and the result of one live
API call; exit code 0 means the server side is healthy, so the problem is host config.
## Develop
```sh
python -m venv .venv && . .venv/bin/activate
pip install -e ".[dev]"
ruff check .
pytest
```
The HTTP query layer is pure stdlib and unit-tested (`tests/test_query.py`); the MCP transport is
driven end-to-end with an in-memory client (`tests/test_server.py`), including a schema-regression
test that pins host-safe tool shapes; the `--check` doctor mode is covered by `tests/test_check.py`.
The `mcp` package is a runtime dependency, so all suites run in CI.
## License
MIT — see [LICENSE](./LICENSE).
Lo que la gente pregunta sobre ingestion-mcp
¿Qué es kenda-co/ingestion-mcp?
+
kenda-co/ingestion-mcp es mcp servers para el ecosistema de Claude AI con 0 estrellas en GitHub.
¿Cómo se instala ingestion-mcp?
+
Puedes instalar ingestion-mcp clonando el repositorio (https://github.com/kenda-co/ingestion-mcp) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar kenda-co/ingestion-mcp?
+
kenda-co/ingestion-mcp aún no ha sido auditado por nuestro agente de seguridad. Revisa el repositorio original en GitHub antes de usarlo en producción.
¿Quién mantiene kenda-co/ingestion-mcp?
+
kenda-co/ingestion-mcp es mantenido por kenda-co. La última actividad registrada en GitHub es de today, con 0 issues abiertos.
¿Hay alternativas a ingestion-mcp?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
Despliega ingestion-mcp en tu cloud
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