Mycelium
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DATAHUB_GMS_URL | No | The URL of the DataHub GMS endpoint. | |
| DEEPSEEK_API_KEY | No | API key for DeepSeek LLM (optional, for narrative). | |
| MYCELIUM_BACKEND | No | The backend to use: 'snapshot' (offline) or 'live' (production). Default is 'snapshot'. | snapshot |
| ANTHROPIC_API_KEY | No | API key for Anthropic Claude LLM (optional, for narrative). | |
| DATAHUB_GMS_TOKEN | No | The authentication token for DataHub. | |
| MYCELIUM_WRITEBACK_ENABLED | No | Enable writeback to DataHub (true/false). Default is false. | false |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| mycelium_triageA | Triage a data incident end to end: cause, severity, blast radius, owner, next actions. Use this instead of What comes back is computed from DataHub, not inferred: the severity (P1-P4) with the inputs
that produced it and the rule that combined them, the assets downstream and how many of them a
person actually watches, the cause with its lineage path and evidence, the owner or the
escalation path when there is no owner, a timeline, ranked next actions, and -- importantly --
a Three things worth knowing before you act on it:
|
| mycelium_askA | Route a question and answer it if it does not need deliberation. Start here for every question. Lookups ("who owns X", "is X fresh", "what columns does X
have") come back answered, with zero model calls and no context spent. Anything genuinely
open-ended comes back marked for investigation, at which point use If the router escalated because the entity was ambiguous, the reasons say so -- resolve that with the user before investigating, rather than investigating the wrong asset thoroughly. |
| mycelium_forageA | Walk the lineage graph on a budget and return a ranked shortlist of what to look at. This is not a lineage dump. Every candidate is fetched at forest resolution only -- the walk is deciding where to read, not reading. Results come back best-first, each with the trail that reached it. Treat the ranking as a hypothesis. Investigate the top three; note the rest without reading them. An empty result is a real finding: it means the cause is outside the hop budget or the direction was wrong, not that there is no cause. |
| mycelium_zoomA | Materialise one entity at a chosen level of detail, and admit it to working memory. Default to At most four entities sit at leaf resolution at once. If you need a fifth, the least-used one is demoted to make room; that is the mechanism working, not a failure. If the response says columns were truncated, quote the stated count rather than concluding a column is absent. |
| mycelium_stepA | Advance the reasoning loop one step: decay activation, demote, prune. Call this between phases of a long investigation. Anything you have not referenced for
three steps leaves working memory -- and is retrievable with |
| mycelium_recallA | Bring something back that was pruned. Nothing was ever destroyed, only set down. Cheaper than re-foraging or re-zooming, so prefer this over hoarding context "in case" -- hoarding is what degrades your own reasoning. |
| mycelium_reinforceA | Lay pheromone on the trails that reached these entities. This is the step that makes the next investigation cheaper. Be honest about the list: reinforcing something you merely looked at teaches the network a wrong path, and it will keep sending agents there for weeks. An empty reinforcement is better than a padded one. |
| mycelium_statsB | What the network has learned, and what is currently in mind. Useful mid-investigation to see how much of the budget is left, and after one to see which paths the catalogue's traffic has carved. |
| mycelium_writebackA | Write the learned hot paths back into DataHub as a knowledge-base document. Turns a private optimisation into shared context: the catalogue that fed the agent gets
better because the agent used it. Requires |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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