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  1. Home
  2. 🧠 Knowledge & Memory
  3. Agent Knowledge
Agent Knowledge logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 9:00:50 PM

Agent Knowledge

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository17 GitHub StarsTotal stargazers on GitHub for the source repository (17 stars).Visit Website

Cross-session memory for AI agents - knowledge graph, scoring, semantic search

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "agent-knowledge": {
      "command": "npx",
      "args": [
        "agent-knowledge"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (6) Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Capabilities & Tool Schemas (6) ~70 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Agent Knowledge.

knowledge

List entries by category and/or tag

knowledge_search

General hybrid TF-IDF + semantic (no `scope`)

knowledge_session

List sessions with metadata

knowledge_graph

Create/update edge between entries

knowledge_analyze

Find near-duplicate entries

knowledge_admin

Vector store statistics

Documentation Overview

agent-knowledge

License: MIT Node >= 20 Tests: 563 passing MCP Tools: 6 LongMemEval R@5: 98.8%

Cross-session memory and recall for AI coding assistants -- works with Claude Code, Cursor, OpenCode, Cline, Continue.dev, and Aider out of the box. Git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing.

Benchmark: R@5 = 97.2% (sparse) / 98.8% (hybrid) on longmemeval_s and 86.0% (sparse) / 88.4% (hybrid) on the harder longmemeval_m split β€” the public LongMemEval academic benchmark (Wu et al. 2024, ICLR 2025), full 500 questions per split, no LLM, no API key, runs entirely offline. +8.6pp to +13.2pp R@5 over the paper's official flat-bm25 baseline in apples-to-apples reproduction. Full per-category table, reproduction instructions, and paper-comparison details in bench/README.md.

Knowledge Base (light)Session Search
Knowledge base with category filteringTF-IDF ranked session search

Why

AI coding sessions are ephemeral. When a session ends, everything it learned -- architecture decisions, debugging insights, project context -- is gone. The next session starts from scratch.

agent-knowledge solves this with two complementary systems:

  1. Knowledge Base -- a git-synced markdown vault of structured entries (decisions, workflows, project context) that persists across sessions and machines.
  2. Session Search -- TF-IDF ranked full-text search across session transcripts from all your coding tools, so agents can recall what happened before -- regardless of which tool was used.

Supported Tools

Sessions from all major AI coding assistants are auto-discovered -- if a tool is installed, its sessions appear automatically.

ToolFormatAuto-detected path
Claude CodeJSONL~/.claude/projects/
CursorJSONL~/.cursor/projects/*/agent-transcripts/
Codex CLIJSONL~/.codex/projects/
AiderMarkdown/JSONL.aider.chat.history.md / .aider.llm.history in project dirs
Continue.devJSON~/.continue/projects/
ClineJSONVS Code globalStorage saoudrizwan.claude-dev/tasks/
OpenCodeSQLite~/.local/share/opencode/opencode.db (or $OPENCODE_DATA_DIR)

No configuration needed. Additional session roots can be added via the AGENT_KNOWLEDGE_EXTRA_SESSION_ROOTS env var (comma-separated paths).

Features

  • Host-agnostic session search -- unified search across every major AI coding assistant (Claude Code, Cursor, Codex CLI, Aider, Continue.dev, Cline, OpenCode). No host name is baked into configuration β€” the adapter registry probes installed host roots at startup.
  • Hybrid search -- semantic vector similarity blended with TF-IDF keyword ranking
  • Git-synced knowledge base -- markdown vault with YAML frontmatter, auto commit and push on writes
  • Automatic staleness detection -- knowledge_analyze(action: "stale_by_code_activity") cross-references file paths mentioned in each entry body against filesModified in recent session summaries. Pairs with a symbol-presence precision layer: identifiers the entry quotes (inline backticks + fenced blocks) are checked in the touched file; if they still exist, confidence downweights Γ—0.3. Entries with evergreen: true are exempt.
  • Search-gap tracking -- knowledge_analyze(action: "search_gaps") surfaces zero-result queries over the last since_days, grouped by token-Jaccard similarity. The clearest signal for "what entries should I write next?".
  • Section-priority context packer -- knowledge(action: "wakeup") assembles a multi-section bundle (identity β†’ active_tasks β†’ recent_decisions β†’ known_gotchas β†’ last_session_summary β†’ top_weighted β†’ semantic_fallback) within a token budget (default 800, override via token_budget or AGENT_KNOWLEDGE_WAKEUP_BUDGET). Unused section budget redistributes to later sections.
  • Scored + gated promoter -- session insights promoted via a 6-signal weighted scorer with three independent gates (minScore, minRecallCount, minUniqueQueries). Runs automatically in background, on demand via knowledge_admin(action: "promote"), or benchable offline via npm run bench:promote. Emits an auditable .dreams/YYYY-MM-DD.md diary every run.
  • Pluggable adapter system -- add support for new tools by implementing the SessionAdapter interface
  • Embeddings -- local (Hugging Face), OpenAI, Claude/Voyage, or Gemini providers
  • Fuzzy matching -- typo-tolerant search using Levenshtein distance
  • 6 search scopes -- errors, plans, configs, tools, files, decisions
  • 6 MCP tools -- consolidated action-based interface (knowledge, knowledge_search, knowledge_session, knowledge_graph, knowledge_analyze, knowledge_admin)
  • Evergreen entries -- evergreen: true in frontmatter exempts an entry from decay in ranking AND makes it append-only under promotion. Dashboard renders a push-pin badge on these cards.
  • Author attribution -- optional author: <string> frontmatter surfaces as a muted chip on each card.
  • Code graph resolution -- calls, imports, inherits edge types for code structure; directed BFS traversal (outbound/inbound/both); bulk_link for efficient ingestion; unlink_by_origin for clearing stale code edges before re-ingest; code: prefixed node IDs distinguish code from knowledge
  • Temporal knowledge graph -- edges support valid_from / valid_to validity windows; as_of queries return point-in-time snapshots; invalidate action marks facts as ended without deleting them
  • Hybrid scoring boosts -- proper-noun and temporal-proximity boosts on top of TF-IDF + semantic blend, capped at +66.7%, short-circuit when no signals are present
  • Category as boost (not filter) -- opt into category_mode: "boost" so a wrong category guess down-ranks instead of discarding the right answer
  • Verbatim session indexing -- per-message chunks (β‰₯30 chars) embedded into the vector store so raw conversation is retrievable; toggle with AGENT_KNOWLEDGE_INDEX_VERBATIM=false
  • Configurable git URL -- knowledge_admin(action: "config") for runtime setup, persisted at XDG/AppData location
  • Cross-machine persistence -- knowledge syncs via git, sessions read from local storage of each tool
  • Real-time dashboard -- browse, search, and manage at localhost:3423
  • Secrets scrubbing -- API keys, tokens, passwords, private keys automatically redacted before git push
  • Knowledge graph -- relationship edges between entries (related_to, supersedes, depends_on, contradicts, specializes, part_of, alternative_to, builds_on) with BFS traversal
  • Confidence/decay scoring -- entries scored by access frequency and recency; auto-promotion from candidate to established to proven
  • Memory consolidation -- TF-IDF duplicate detection on write (warns of similar entries) plus knowledge_analyze(action: "consolidate") for batch dedup scanning
  • Reflection cycle -- knowledge_analyze(action: "reflect") surfaces unconnected entries and generates structured prompts for the agent to identify new graph connections
  • Auto-linking on write -- new entries automatically linked to top-3 similar existing entries when cosine similarity > 0.7
  • Confidence metadata β€” entries tagged extracted (user-written) or inferred (auto-distilled, 0.85Γ— search rank multiplier); confidence_score field carries the model's certainty 0-1
  • Knowledge analysis β€” knowledge_analyze actions god_nodes (most-connected entries), bridges (cross-category connectors), gaps (isolated entries)
  • Knowledge brief β€” knowledge_analyze(action: "brief") returns a cached ~200 token summary (core concepts, active projects, recent decisions, stale and gap counts) for session-start orientation
  • Edge provenance β€” graph edges track origin (manual, auto-link, distill, reflect) so analysis can distinguish user judgment from automated heuristics
  • Deterministic pre-extraction in distillation β€” session summaries now include git commits, error patterns, URLs accessed, and packages changed extracted via regex from bash/tool output (no LLM cost)
  • Freshness metadata on every search hit β€” every knowledge result carries freshness: { body_age_days, last_accessed, access_count, verified_at, verification_age_days, evergreen }. Agent reads the trust signal and decides; we impose no policy demotion.
  • Per-category decay windows β€” the "Unused" filter and bytype chart honor per-category thresholds (projects 180d, people 365d, decisions 90d, workflows 60d, notes 30d) so identity-shaped content doesn't look stale just because it isn't re-read weekly.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
17
Stargazers on the source repository.
Last commit
4mo ago
Most recent push to the default branch.
Tools exposed
6
Callable tools this server registers over MCP.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Agent Knowledge

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "agent-knowledge": { "command": "npx", "args": ["-y", "agent-knowledge"] } }

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedApr 21, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars17
GitHub Star CountTotal stargazers on GitHub representing community popularity (17 stars).
Last commit4mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Apr 21, 2026
49Quality signal: Fair Β· 49/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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