v0.9.0 - Applicable, Compositional Memory

Agent Memory Bridge 0.9 keeps the same small MCP bridge while the engine underneath
gets more structured and more applicable.

Thesis

0.9.0 = applicable, compositional memory on top of a still-small MCP surface.

The public MCP surface is still the same 10 tools:

• store
• recall
• browse
• stats
• forget
• promote
• claim_signal
• extend_signal_lease
• ack_signal
• export

What changed is the engine behind that bridge.

What Shipped

• relation-lite metadata surfaced through recall, export, stats, proof, and health tooling
• benchmarked retrieval with precision@k, recall@k, MRR, and expected_top1_accuracy
• metadata-only telemetry plus client/model provenance
• first-pass task-time assembly over procedures, concept notes, beliefs, and linked supporting records
• the planned 0.8 structure and credibility work folded into the direct 0.9.0 release

Evidence

Current release snapshot:

• pytest: 152 passed
• deterministic proof: 4/4 checks passed
• canonical benchmark:
  • question_count = 11
  • memory_expected_top1_accuracy = 1.0
  • memory_mrr = 1.0
  • file_scan_expected_top1_accuracy = 0.636
  • file_scan_mrr = 0.909
  • relation_metadata_passed = true
  • duplicate_suppression_rate = 1.0

Reviewed classifier calibration snapshot:

• sample_count = 16
• classifier_exact_match_rate = 0.875
• fallback_exact_match_rate = 0.062
• classifier_better_count = 13
• fallback_better_count = 2
• classifier_filtered_low_confidence_count = 2

Why It Matters

This release makes the bridge more useful without turning it into a bigger platform.

• Memory is more structured than transcript capture.
• Retrieval claims are benchmarked instead of guessed.
• Task-time recall can assemble procedures, concepts, beliefs, and linked support.
• The public integration contract stays small and inspectable.

Honest Boundaries

0.9.0 does not mean:

• a graph database
• full relation-aware traversal or ranking across the whole store
• automatic procedure learning from raw transcripts
• a scheduler or agent runtime
• cross-domain concept synthesis

Next

The next pressure points are broader reviewed fixtures, deeper cross-record assembly,
more deliberate procedure promotion, and pre-compaction capture before model-side loss.