Transforms ArcRift into a universal memory layer accessible from any MCP-compatible AI tool: Claude Code, Cursor, Windsurf, Claude Desktop. Exposes tools for retrieving relevant memory, storing long-term memory, semantic search, project management, and knowledge graph operations.
ArcRift exposes 8 tools with complete input schemas and descriptions. Naming follows verb_noun convention (recall_, store_, prune_, search_, list_, get_, identify_, index_). Descriptions are substantive (100-200 chars), explaining WHAT and WHEN. However, output schemas are not documented in the visible code, LLMs cannot predict response structure. Parameter descriptions are present but lack constraints (enums, ranges, formats). Error handling and recovery guidance are absent. No tool annotations (readOnlyHint, destructiveHint) despite clear risk levels. Security concerns: prune_memory and index_codebase are destructive but lack confirmation patterns.
Get a structured knowledge-graph summary for a project.
Automatically identify the ArcRift project ID based on a folder path or CWD.
Scans a local directory and indexes the raw source code files into the current session's memory graph. Call this to give the AI access to the actual codebase.
List all project names and IDs stored in ArcRift Memory.
Surgically remove facts or context chunks from a project. Use this to correct errors or tell ArcRift to 'forget' outdated info.
Retrieve the most relevant memory chunks for a given prompt. Returns sanitised chunks wrapped in <ARCRIFT_retrieved_context> delimiters.
Output schemas not documented. LLMs cannot predict response structure for any tool. Responses must include field names, types, and examples so agents can chain calls and extract data reliably.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). prune_memory and index_codebase are destructive but unmarked. Agents cannot distinguish safe reads from irreversible writes.
No confirmation or dry-run pattern for destructive operations. prune_memory and index_codebase modify state without user confirmation. Agents can accidentally delete data or index wrong directories.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 65 | <=2025-11-25 | v2 |
Semantic search across all sessions and projects.
Save text or a full conversation transcript to ArcRift long-term memory. This updates the Knowledge Graph and makes the chat visible in the Dashboard history. Use this to 'save' a coding session or a key decision.
Parameter constraints missing. topN accepts 'max 6' but no enum or min/max in schema. project parameter is optional but semantics unclear (what happens if omitted?). No format validation for directoryPath (absolute vs relative).
No error recovery guidance. Tools lack descriptions of failure modes, retryability, or next steps. E.g., if recall_context finds no chunks, should the agent retry with different prompt or call search_memory instead?