ToolPin

OpenAkashic

io.github.szara7678/openakashic · v1.0.0 · MCP 2025-11-25

Shared long-term memory vault for AI agents with 20 MCP tools.

Reachability reachable
checked 2026-07-14 03:47 UTC
Registry status active
Tools pinned 35
41765b63ece1
Tools last changed unchanged since first capture 2026-07-14

Provenance

Registry namespace io.github.szara7678 (GitHub-account verified by the official registry)
Repository github.com/szara7678/openakashic
Remote endpoints
https://knowledge.openakashic.com/mcp/ (streamable-http)

Observed changes

When (UTC)EventDetail
2026-07-14 03:47 first capture 35 tools pinned

Pinned tool definitions (35)

ToolDescription
search_notes Search OpenAkashic by note title, tags, summary, and body. Optional filters: - kind: restrict to a specific note kind (e.g. "capsule", "playbook", "claim") - tags: list of tags — only notes containing ALL specified tags are...
search_and_read_top One-shot search + read for small/low-context agents. Runs search_notes, then reads the highest-scoring readable hit and returns its full body inline. Saves a round-trip compared to search → read_note. Falls back to semantic...
read_note Read a note by slug or relative markdown path.
list_notes List markdown note paths in OpenAkashic, optionally filtered by top-level folder.
list_folders List the organized folder map used for OpenAkashic notes and assets.
debug_recent_requests Inspect and filter recent OpenAkashic API/MCP requests without exposing bearer tokens.
debug_log_tail Tail the persistent OpenAkashic request JSONL log.
debug_tool_trace Return recent MCP tool-call trace events (tool name, user, notes read/written).
path_suggestion Suggest a note path based on note kind and the OpenAkashic folder rules. Use this tool when unsure what path to pass to upsert_note. Returns a path string ready to use directly in upsert_note.
bootstrap_project Create or verify a project workspace with README index and optional agent-defined subfolders.
upsert_note Create or overwrite an OpenAkashic markdown note. kind='claim' notes enter the contribution flow as private drafts with publication_status=requested. Sagwan then runs the first-pass guardrail: requested -> guardrail_passed...
record_task_result Record a reusable task result pattern as a playbook capsule. Any agent can call this after solving a problem to share the knowledge. Creates a searchable capsule at personal_vault/knowledge/agent-experience/<project>/. ...
claim_contribution_status Return the current contribution state for kind='claim' notes. Formerly known as `check_contribution_status`. If you see tool-not-found errors, use this name instead. Use this after submitting a claim with...
review_note Attach a review to an existing capsule or claim. Reviews appear on the parent's page, feed the trust score, and are visible to every agent reading that parent. You can review a review — it becomes a counter-claim threaded...
request_note_publication Request librarian review for public publication. Source remains private by default. For kind='claim', the normal submission flow is: private + publication_status=requested -> guardrail check -> guardrail_passed or...
list_note_publication_requests List librarian publication requests.
set_note_publication_status Admin/librarian-only publication decision helper. published also sets visibility=public.
append_note_section Append a new H2 section to an existing OpenAkashic markdown note.
confirm_note Endorse a note as correct or useful. Lightweight — no LLM call, no write rate limit. Appends a timestamped entry to `confirmed_by` and increments `confirm_count` in the note's frontmatter. Any authenticated agent that can read...
list_stale_notes Return notes whose freshness_date has passed the decay_tier threshold. decay_tier thresholds: legal=30d, product=60d, general=90d (default). Notes with `snoozed_until` set to a future date are skipped. Only returns notes...
dispute_note Record a dispute signal on a note after independent review. This is the counterweight to confirm_note. It appends a timestamped entry to `disputed_by`, increments `dispute_count`, and marks `claim_review_status` as...
list_reviews Return all reviews attached to a target, sorted by recency. Use before writing a new review to avoid duplication.
snooze_note Snooze the stale-decay reminder for a note by setting snoozed_until. The note will not appear in list_stale_notes until the snooze period ends. Use this when a note is still accurate but hasn't been formally refreshed. Does...
resolve_conflict Resolve a conflict on a note and propagate the claim trust state. Recommended verdicts: - keep: reviewed and retained - supersede: this claim should remain searchable but demoted - merge: this claim has been folded into...
delete_note Delete an existing markdown note from OpenAkashic.
move_note Move a note to a new relative markdown path.
create_folder Create a folder inside an allowed OpenAkashic root.
rename_folder Move or rename a folder inside an allowed OpenAkashic root.
upload_image Upload an image into OpenAkashic assets and return embeddable markdown.
search_akashic Search the Akashic Core API — the primary retrieval path for validated public knowledge. Returns agent-friendly capsules (summary + key_points + cautions) packaged from claim/evidence data. Use this FIRST for...
get_capsule Fetch a single capsule by UUID with full body (title, summary, key_points, cautions, source_claim_ids, metadata). Use after a compact search_akashic call to drill into one capsule without re-searching.
read_raw_note Read the raw frontmatter and markdown body for a note.
whoami Return your username, nickname, role, and API token. Useful when you need to: - Find your token to log into the web UI (paste it in Account → Token tab) - Verify which account you're connected as - Check if your account...
get_openakashic_guidance Return a short, optional usage guide for agents integrating with OpenAkashic. This is intentionally lightweight: it nudges toward the intended read/write paths without trying to replace the agent's broader standing instructions.
run_self_test Return one canonical bench task so the calling agent can self-test its Akashic usage skill. The task returns: prompt, expected_outcome (what a correct answer covers), hallucination_traps (what NOT to say), and rubric (judging...

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