Map the codeand the docs behind it.
Graphify links your code to the design docs, PDFs, Office files and recordings that explain it, then flags pull requests that collide. codebase-memory-mcp indexes code very wide and very fast: 162 languages from one static binary.
Checked against the codebase-memory-mcp README on 14 October 2026.
Four reasons teams pick Graphify.
- 01
The docs that explain the code, in the same graph
Design docs, PDFs, Office files and images are read for the concepts and decisions in them, then linked to the functions they describe. Audio and video are transcribed on your machine and join too.
How codebase-memory-mcp compares. It parses Markdown as a language. PDFs, Office files and media are not in its README.
- 02
A report a person can read
GRAPH_REPORT.mdnames the god nodes, the communities, the surprising connections and the questions worth asking.graph.htmlopens in any browser, and the graph exports to Neo4j, FalkorDB, GraphML, Obsidian, SVG and Mermaid.How codebase-memory-mcp compares. CBM Lens, a beta browser viewer, and a shared SQLite file for the team. No export formats are listed.
- 03
Pull requests that collide, caught before merge
graphify prs --conflictslists the open pull requests that reach into the same parts of the graph, with the merge-order risk. On Graphify Cloud the same check runs on every pull request.How codebase-memory-mcp compares.
detect_changesmaps one diff to the symbols it affects, with a risk class. - 04
A solver checks changed functions
On Graphify Cloud, each changed function is checked against the version it replaces. The answer is proven, changed (with the input that shows it and a regression test) or unknown. The free plan includes one run a day.
How codebase-memory-mcp compares. Verification is not in its README.
Graphify and codebase-memory-mcp, row by row.
The open-source graphify CLI against the open-source codebase-memory-mcp first. The last two rows are Graphify Cloud.
Pick by what your agents need to read.
Choose Graphify if
- Your agents need the design docs, specs and recordings that explain the code
- You want a written report and exports to Neo4j or Obsidian for people, too
- Several people or agents open pull requests against the same repository
- You want a solver to check changed functions before they merge
- You want a hosted option with a free plan
Choose codebase-memory-mcp if
- You work in a language outside Graphify's 36; it ships 162
- You want Cypher-like queries or embedding search over code
- You map Docker, Kubernetes and Helm, or HTTP and gRPC calls between services
Run both on your own repository.
Install Graphify with uv tool install graphifyy (or pip install graphifyy), run graphify install to register the /graphify skill with the assistants it finds, then type /graphify . in your assistant. Code maps on your machine with no API key.
Both tools are MCP servers, so one assistant can hold both. Ask each the questions your team asks every week, and keep the one that answers them.
Graphify vs codebase-memory-mcp: questions
What people ask when they are choosing a code graph.
When the answer depends on more than the code, yes. Graphify links your code to the design docs, PDFs and recordings that explain it, writes a report a person can read, flags pull requests that collide, and on Graphify Cloud checks changed functions with a solver. When you need a language outside Graphify's 36, or Cypher queries over code alone, codebase-memory-mcp covers more ground.
The open-source graphify CLI (the graphifyy package, Apache 2.0) against the open-source codebase-memory-mcp (MIT), as each README described them on 14 October 2026. The pull request review and verification rows are Graphify Cloud, which has a free plan with no card. codebase-memory-mcp has no hosted product.
Nobody has run both on the same tasks yet, us included. codebase-memory-mcp reports about 120 times fewer tokens than file-by-file search on five queries. Its preprint across 31 repositories reports 10 times fewer tokens, with answer quality of 83% against 92% for file-by-file exploration. Graphify's published code result measures accuracy: on ERPNext, about a million lines, one Graphify tool raised key-fact coverage from 70.8% to 82.0% against grep and file reads, on six graded questions.
Yes. Both are MCP servers, so one assistant can hold both while you decide. Most teams then make one the default for structural questions, so the agent is not weighing two answers to the same question.
Run locally, neither sends your source code anywhere, and neither collects usage data. Graphify parses code on your machine. Docs, PDFs and images go to the model you pick for the semantic pass, which can be a local Ollama. Graphify Cloud, if you use it, builds the graph on Graphify's servers.
The open-source CLI is free under Apache 2.0 and needs no account. Graphify Cloud has a Free plan with no card: 3 repositories, 15 pull request reviews a month and one verification run a day. Pro and Teams raise those limits.
codebase-memory-mcp rows come from its README at github.com/DeusData/codebase-memory-mcp and its preprint, read on 14 October 2026. Graphify rows come from the graphify README, its BENCHMARKS.md and pricing. codebase-memory-mcp belongs to its authors; Graphify Labs is not affiliated with it. Spotted something out of date? Tell us on GitHub.
More comparisons: Graphify vs CodeGraph, Graphify vs code-review-graph, Graphify vs Sourcegraph, all comparisons.