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MCP server · RAG

Knowerage

Local MCP server that tracks AI analysis coverage against your codebase

Unclaimed rag
34Low

Scored 5 months ago · breakdown

About Knowerage

Knowerage is an MCP server published by MTimma in the RAG category: local MCP server that tracks AI analysis coverage against your codebase.

The repository has 3 stars and 0 forks, with the last commit 5 months ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/MTimma/knowerage

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (10)

knowerage_create_or_update_docCreate/update analysis document

Parameters not published.

knowerage_generate_bundleChunked export of selected analyses (`toc*.md`, `combined*.md`, `manifest.json`)

Parameters not published.

knowerage_get_file_statusAnalyzed vs missing ranges

Parameters not published.

knowerage_get_treeTree/grouped coverage

Parameters not published.

knowerage_list_registryFull registry snapshot (same shape as `registry.json`, sorted keys)

Parameters not published.

knowerage_list_staleList stale/problematic records

Parameters not published.

knowerage_parse_doc_metadataParse and validate frontmatter

Parameters not published.

knowerage_reconcile_allFull rescan/rebuild

Parameters not published.

knowerage_reconcile_recordReconcile one analysis record

Parameters not published.

registry_export_reportExport snapshot (JSON/YAML/TXT/HTML)

Parameters not published.

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Security checks

  • ✓README presentThe repository ships documentation.

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README

Knowerage — AI Analysis Coverage Management

Links: GitHub · Glama MCP listing · npm @mtimma/knowerage

Quick Start

Requirements: Node.js 18 or newer — npx must be on your PATH (it comes with npm, which is included with Node).

MCP server configuration

Register Knowerage wherever your MCP host expects server definitions (for example some clients use .cursor/mcp.json or .vscode/mcp.json; others use environment variables or a UI—follow your host’s documentation). Use the same server entry shape:

{
  "mcpServers": {
    "knowerage": {
      "command": "npx",
      "args": ["@mtimma/knowerage"],
      "env": {
        "KNOWERAGE_WORKSPACE_ROOT": "${workspaceFolder}",
        "KNOWERAGE_AUTO_FULL_RECONCILE": "true"
      }
    }
  }
}

Replace ${workspaceFolder} with your project root if your host does not expand that variable.

KNOWERAGE_AUTO_FULL_RECONCILE is optional: when unset, empty, or not a truthy value, the file watcher defaults to off. Set to 1, true, yes, or on (trimmed, case-insensitive) to enable. When on, the server watches knowerage/ and, after a short debounce, runs knowerage_reconcile_all on filesystem changes. That is not the same as running a full reconcile after every MCP tool call—it only reacts to file changes under knowerage/. Registry writes to registry.json are ignored by the watcher so saves do not loop.

How to use Knowerage

After the MCP server is configured, you talk to your assistant in normal sentences. You do not need to memorize tool names.

Analyse or document code

Point at files, classes, or behaviour you care about. For example:

  • Using Knowerage, analyse the logical algorithm workflow in main.java.
  • Analyze the data entity reconciliation and versioning logic in the ETL service.

The assistant creates or updates markdown under knowerage/analysis/ and records coverage in knowerage/registry.json (see How It Works below).

Coverage and gaps (same project, later chat or another agent)

When you already have analyses in the tree, you can ask:

  • In percentage, how much of the code has our analysis covered?
  • What part of this codebase is not yet analysed?

Knowerage answers these from the registry and coverage helpers (for example overview, per-file status, and stale lists)—not from hand-waving over the repo.

Alternative approaches

Install via npm

npx @mtimma/knowerage

Or build from source

cargo build --release
./target/release/knowerage-mcp

How It Works

  1. AI agent creates analysis .md files with YAML frontmatter declaring source file and covered line ranges
  2. Registry (knowerage/registry.json) tracks analysis records with SHA-256 hashes for freshness
  3. MCP tools expose create, reconcile, query, and export operations
  4. Agent says "analyze X" → full workflow runs automatically (create → reconcile → record)

Registry file shape (knowerage/registry.json)

The on-disk format is a JSON object whose keys are analysis paths (strings). Each value is one record (see contracts/contracts.md). A full sample with two records lives at examples/registry.sample.json.

flowchart TB
  subgraph file["knowerage/registry.json"]
    O["Top-level JSON object"]
    O --> K["Each key: analysis markdown path, e.g. knowerage/analysis/.../topic.md"]
    K --> V["Value: one RegistryRecord"]
  end

  subgraph rec["RegistryRecord fields"]
    ap["analysis_path · source_path"]
    cr["covered_ranges: [[start,end], ...]"]
    h["analysis_hash · source_hash (sha256:… )"]
    t["record_created_at · record_updated_at (ISO 8601)"]
    st["status: fresh | stale_doc | stale_src | missing_src | dangling_doc"]
  end

  V --> rec

Frontmatter for analysis .md files is specified separately in the contracts doc (metadata schema), not inside registry.json.

MCP Tools

Tool Purpose
knowerage_create_or_update_doc Create/update analysis document
knowerage_parse_doc_metadata Parse and validate frontmatter
knowerage_reconcile_record Reconcile one analysis record
knowerage_reconcile_all Full rescan/rebuild
knowerage_get_file_status Analyzed vs missing ranges
knowerage_list_stale List stale/problematic records
knowerage_list_registry Full registry snapshot (same shape as registry.json, sorted keys)
knowerage_get_tree Tree/grouped coverage
registry_export_report Export snapshot (JSON/YAML/TXT/HTML)
knowerage_generate_bundle Chunked export of selected analyses (toc*.md, combined*.md, manifest.json)

Project Structure

knowerage/                  # Created per-project
├── analysis/              # Analysis markdown files
│   └── **/*.md
└── registry.json          # Coverage registry

src/                       # Rust MCP server
├── main.rs
├── lib.rs
├── types.rs
├── parser.rs
├── registry.rs
├── mcp.rs
├── security.rs
└── export.rs

Documentation

Security

  • All paths validated against workspace root
  • Path traversal (..) rejected
  • Atomic writes for registry (crash-safe)
  • No secrets in analysis files or reports
  • SHA-256 hash-based freshness (survives git pull)

License

MIT — copyright Martins Timma.

Parts of this project were written or refined with generative AI coding assistants. Human review applies to design, security-sensitive behavior, and releases.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Knowerage

How do I install Knowerage?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Knowerage safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Knowerage still maintained?

Yes — the last commit was 5 months ago. The repository has 3 stars and 0 forks.