Skip to main content
Glama
deenesjakoruzh
scarletkc

Perenna

by scarletkc
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Perenna

Python PyPI CI Codecov CodeRabbit Pull Request Reviews License Ask DeepWiki

perenna MCP server

Лёгкая, постоянная память на Git для ИИ-агентов. Claude Code, Codex, ChatGPT, Cursor и другие MCP-клиенты могут обмениваться долговременными воспоминаниями, не разделяя учётную запись поставщика или историю разговоров.

  • Отдельные MCP-инструменты для чтения, записи и удаления воспоминаний

  • Локальные транспорты stdio и однопользовательские Streamable HTTP-транспорты с защитой OAuth

  • Человекочитаемый Markdown в независимом Git-репозитории

  • Локальный поисковый индекс Vexor, который всегда можно пересоздать из Git

  • Межпроцессная блокировка для нескольких локальных процессов агентов

Почему Perenna?

Ваша память должна следовать за вами, а не за агентом, которым вы пользуетесь.

Claude Code, Codex, Cursor и ChatGPT хранят память в отдельных изолированных хранилищах. Смените агента — и ваша память исчезнет. Смените машину — и локальная память останется позади.

Perenna даёт им общую память на базе Git. Локальные агенты и ChatGPT могут подключаться к одному и тому же самостоятельно размещённому сервису Perenna, а каждое долговременное воспоминание остаётся обычным Markdown, который вы можете просматривать, редактировать, версионировать и резервировать самостоятельно.

Самостоятельно размещаемый стек Mem0 значительно тяжелее, а его облачный бесплатный тариф в настоящее время допускает использование контента клиентов для обучения моделей и улучшения продукта.

Perenna отличается по своей сути: без учётной записи, без проприетарного облака для памяти, без привязки к вендору. Просто ваши воспоминания, в вашем Git-репозитории, на инфраструктуре, которую вы контролируете.

Related MCP server: phren

Быстрый старт

Установка с помощью вашего ИИ-агента

Вставьте это в Claude Code, Codex, ChatGPT Desktop, Cursor или другого агента для работы с кодом, имеющего доступ к терминалу и локальной конфигурации MCP:

Install Perenna and connect it to this AI agent as a local stdio MCP server.
Work through the complete setup autonomously.

Use these as the source of truth:
- https://github.com/scarletkc/Perenna/blob/main/docs/getting-started.md
- https://github.com/scarletkc/Perenna/blob/main/docs/guides/client-setup.md

1. Detect the operating system, shell, and current MCP client.
2. Check for Python 3.12 or newer, Git, and uv. Install uv in user scope if it
   is missing. If Python or Git needs administrator approval, give me the exact
   command and stop there.
3. Install Perenna with `uv tool install perenna`. If Perenna is already
   installed, upgrade it with `uv tool upgrade perenna`.
   For Codex, also run `perenna skill install --agent codex`. For Claude Code,
   run `perenna skill install --agent claude-code`. Do not replace an existing
   modified copy or remove unrelated installed skills.
4. Check the effective Vexor embedding provider configuration. Reuse a working
   `~/.vexor/config.json` or inherited environment configuration. If none is
   available, ask me to choose between a remote provider and local embeddings.
   Explain that a remote provider receives memory text and search queries. For
   a remote provider, keep the provider and model in Vexor configuration and
   supply its secret through `VEXOR_API_KEY` or the provider-specific environment
   variable. For local embeddings, install `perenna[local]` and configure the
   local model according to the Perenna configuration reference. Verify the
   selected provider with `uvx vexor doctor` using the same environment that
   the Perenna process will inherit.
5. Ask whether I want to synchronize Perenna with a private Git repository. If
   I do, ask me to provide or approve its URL, run
   `perenna sync setup <repository-url>`, and verify it with
   `perenna sync status`. Treat repository creation, remote replacement, and
   reconciling diverged history as separate choices that require my explicit
   approval.
6. Register `perenna mcp --source <stable-client-name>` using the client-specific
   method in the setup guide. Preserve unrelated MCP servers and settings. Use
   a stable source such as `claude-code`, `codex`, or `cursor` for this client.
   For another client, use its official instructions for adding a local stdio
   MCP server. Make sure the Perenna process inherits `VEXOR_CONFIG_JSON`,
   `VEXOR_API_KEY`, or any provider-specific key used in step 4. Report only
   whether a secret is present.
7. Verify `perenna --help` and the saved MCP configuration. Reload MCP servers
   and call `memory_read` with `action: "list"` when the client supports it. If
   a restart is required, tell me the single restart step.
8. Report the commands run, files changed, and verification results. Keep API
   keys out of tracked configuration files.

Установка опубликованного релиза

Для Perenna требуются Python 3.12+, Git и uv.

uv tool install perenna

Установите дополнительный навык поведения памяти для локального клиента:

perenna skill install --agent codex
# or
perenna skill install --agent claude-code

Повторите --agent в одной команде, если навык должны получить оба клиента. В справочнике по конфигурации описаны область действия пользователя и проекта, места назначения и защитные механизмы от перезаписи.

Codex и Claude Code могут вместо этого установить комбинированный навык и MCP-подключение из Marketplace репозитория Perenna. Следуйте руководству по настройке плагина и выберите один путь настройки для каждого клиента.

Для Perenna нужен рабочий провайдер эмбеддингов Vexor. Для интерактивного выбора и настройки провайдера выполните:

uvx vexor init

Perenna автоматически переиспользует ~/.vexor/config.json. При использовании конфигурации на уровне процесса убедитесь, что MCP-сервер получает VEXOR_CONFIG_JSON и либо VEXOR_API_KEY, либо ключ выбранного провайдера из своего хост-окружения. Удалённые провайдеры получают текст воспоминаний и поисковые запросы.

Если вы выбираете локальные эмбеддинги, установите также локальный дополнительный пакет Perenna:

uv tool install "perenna[local]"

Конфигурация провайдера Vexor охватывает удалённую и локальную настройку. В окружении, из которого запускается MCP-клиент, проверьте выбранного провайдера с помощью:

uvx vexor doctor

Настройте MCP-клиент для запуска:

perenna mcp --source <client-name>

Perenna создаёт свои локальные данные в ~/.perenna/, если не задан другой домашний каталог.

Чтобы импортировать, опубликовать или выполнить fast-forward совместимой истории через частный Git-репозиторий, выполните:

perenna sync setup <repository-url>

Установка из исходного кода для разработки

git clone https://github.com/scarletkc/Perenna.git
cd Perenna
uv tool install .

Документация

Начните с индекса документации, затем выберите путь для вашей задачи:

Лицензия

MIT

Available Tools

3 tools
memory_deleteA
Destructive

Delete exactly one committed memory by ID, expected title, and revision. The deletion removes it from current recall but remains recoverable from Git history.

ParametersJSON Schema
NameRequiredDescriptionDefault
memory_idYes
base_revisionYes
expected_titleYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
actionYes
commitYes
memoryYes
changedYes
sync_statusYes
index_statusYes
recoverable_via_gitYes

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructiveHint=true and idempotentHint=false. The description adds valuable non-obvious context: the deletion removes from recall but remains recoverable via Git history, and it deletes 'exactly one' memory. This goes beyond the annotations without contradicting them. It does not mention side effects like concurrency checks, but the added recoverability and scoping are meaningful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one compact sentence that leads with the action and core constraints, then adds the recoverability detail. There is no fluff or repetition; every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive operation with three required parameters and an output schema, the description is thin. It omits behavior on mismatch (e.g., if expected_title or base_revision does not match), error semantics, or any guidance on when this tool should be chosen over siblings. The recoverability note is helpful (something the output schema won't reveal), but other important context is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. However, it only mentions parameters as 'ID, expected title, and revision' without explaining their purpose, format, or how they are used (e.g., what an expected title is for, what a base revision means, or how they act as safety checks). No examples or constraints are provided, leaving agents to infer semantics from names alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Delete'), resource ('one committed memory'), and identifies the parameters by role (ID, expected title, revision). It clearly distinguishes from siblings memory_read and memory_write by the action it performs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives. It only implies deletion use case without mentioning conditions, prerequisites, or exclusions (e.g., 'use memory_read to view' or 'use memory_write to create'). No context is given for when a deletion is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

memory_readA
Read-onlyIdempotent

Read permanent memory. List returns stable memory IDs and titles, search returns bounded ranked candidate passages, and get returns one complete committed memory with its revision.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, non-destructive, idempotent, and open-world behavior. The description adds useful context beyond annotations: search results are 'bounded ranked candidate passages,' list returns only IDs/titles, and get returns a 'complete committed memory with its revision.' No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core purpose and uses parallel clauses to describe each action without redundancy or filler. It is compact yet informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's three modes and the existence of an output schema, the description is complete: it explains the behavior of each action and what kind of result to expect. Annotations cover safety and side-effect concerns, and sibling names make the read/write/delete division clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema fully documents the action variants, required fields, and limit bounds through its oneOf structure and const values. The description does not add parameter-level detail such as query format or memory_id semantics, but with schema coverage effectively complete, the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Read permanent memory') and enumerates three distinct modes—list, search, get—with their concrete outcomes. This distinguishes the tool from memory_write and memory_delete without relying on the name alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells an agent what each mode returns, which is clear guidance for choosing list vs search vs get. It does not explicitly say 'use this instead of memory_write or memory_delete,' but 'Read' and the sibling names make the intended usage obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

memory_writeA
Destructive

Create or modify permanent memory. Summary is a stable one-line description of what a memory covers. Patch applies exact all-or-nothing edits; replace overwrites the complete summary and body. Existing memories require a current base revision.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
actionYes
commitYes
memoryYes
changedYes
sync_statusYes
index_statusYes

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (destructiveHint=true, readOnlyHint=false), the description discloses valuable behavioral details: patch is all-or-nothing, replace overwrites the complete summary/body, and existing memories require a current base revision, implying optimistic concurrency. This does not contradict any annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three dense sentences with no filler. The purpose is front-loaded, and each sentence addresses a distinct aspect: overall behavior, summary semantics, and modifications semantics.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the key operational facts an agent needs: the three modes, the summary convention, patch atomicity, and the base-revision requirement. Since an output schema exists, return-value details are not needed here. A minor gap is not pointing agents to memory_read to retrieve the current base revision.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning beyond the schema by defining summary as a 'stable one-line description', explaining the exact semantics of patch and replace, and mentioning the base revision requirement. This is useful context that the bare schema types do not convey, though title and project are left to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Create or modify') on a clear resource ('permanent memory') and further differentiates the three operational modes: create, patch, and replace. This makes the tool unmistakably the write counterpart to memory_read and memory_delete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides internal guidance on when to use patch vs replace and notes the base-revision prerequisite for modifying existing memories. However, it does not explicitly mention memory_read or memory_delete or state when to prefer this tool over those siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.1.1
    • Changedmemory_read5 fields changed
      • removedInput schema / additionalProperties
        Removed value: -false
      • addedInput schema / oneOf
        Added value: +[
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "list"
+      },
+      "project": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "search"
+      },
+      "limit": {
+        "maximum": 5,
+        "minimum": 1,
+        "type": "integer"
+      },
+      "project": {
+        "type": "string"
+      },
+      "query": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action",
+      "query"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "get"
+      },
+      "memory_id": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action",
+      "memory_id"
+    ],
+    "type": "object"
+  }
+]
      • removedInput schema / properties
        Removed value: -{
-  "action": {
-    "enum": [
-      "list",
-      "search",
-      "get"
-    ],
-    "type": "string"
-  },
-  "limit": {
-    "maximum": 5,
-    "minimum": 1,
-    "type": "integer"
-  },
-  "memory_id": {
-    "type": "string"
-  },
-  "project": {
-    "type": "string"
-  },
-  "query": {
-    "type": "string"
-  }
-}
      • removedInput schema / required
        Removed value: -[
-  "action"
-]
      • changedOutput schema / oneOf
        Previous value: -[
-  {
-    "additionalProperties": false,
-    "properties": {
-      "action": {
-        "const": "list"
-      },
-      "memories": {
-        "items": {
-          "additionalProperties": false,
-          "properties": {
-            "memory_id": {
-              "type": "string"
-            },
-            "scope": {
-              "type": "string"
-            },
-            "summary": {
-              "type": "string"
-            },
-            "title": {
-              "type": "string"
-            }
-          },
-          "required": [
-            "memory_id",
-            "title",
-            "scope",
-            "summary"
-          ],
-          "type": "object"
-        },
-        "type": "array"
-      },
-      "project": {
-        "type": [
-          "string",
-          "null"
-        ]
-      },
-      "projects": {
-        "items": {
-          "type": "string"
-        },
-        "type": "array"
-      }
-    },
-    "required": [
-      "action",
-      "project",
-      "memories",
-      "projects"
-    ],
-    "type": "object"
-  },
-  {
-    "additionalProperties": false,
-    "properties": {
-      "action": {
-        "const": "search"
-      },
-      "limit": {
-        "maximum": 5,
-        "minimum": 1,
-        "type": "integer"
-      },
-      "matches": {
-        "items": {
-          "additionalProperties": false,
-          "properties": {
-            "memory_id": {
-              "type": "string"
-            },
-            "passages": {
-              "items": {
-                "additionalProperties": false,
-                "properties": {
-                  "end_char": {
-                    "minimum": 1,
-                    "type": "integer"
-                  },
-                  "start_char": {
-                    "minimum": 0,
-                    "type": "integer"
-                  },
-                  "text": {
-                    "type": "string"
-                  }
-                },
-                "required": [
-                  "text",
-                  "start_char",
-                  "end_char"
-                ],
-                "type": "object"
-              },
-              "minItems": 1,
-              "type": "array"
-            },
-            "rank": {
-              "minimum": 1,
-              "type": "integer"
-            },
-            "revision": {
-              "type": "string"
-            },
-            "scope": {
-              "type": "string"
-            },
-            "summary": {
-              "type": "string"
-            },
-            "title": {
-              "type": "string"
-            }
-          },
-          "required": [
-            "memory_id",
-            "title",
-            "scope",
-            "summary",
-            "revision",
-            "rank",
-            "passages"
-          ],
-          "type": "object"
-        },
-        "type": "array"
-      },
-      "project": {
-        "type": [
-          "string",
-          "null"
-        ]
-      },
-      "truncated": {
-        "type": "boolean"
-      }
-    },
-    "required": [
-      "action",
-      "project",
-      "limit",
-      "matches",
-      "truncated"
-    ],
-    "type": "object"
-  },
-  {
-    "additionalProperties": false,
-    "properties": {
-      "action": {
-        "const": "get"
-      },
-      "memory": {
-        "additionalProperties": false,
-        "properties": {
-          "body": {
-            "type": "string"
-          },
-          "created_at": {
-            "type": "string"
-          },
-          "memory_id": {
-            "type": "string"
-          },
-          "revision": {
-            "type": "string"
-          },
-          "scope": {
-            "type": "string"
-          },
-          "source": {
-            "type": "string"
-          },
-          "summary": {
-            "type": "string"
-          },
-          "title": {
-            "type": "string"
-          },
-          "updated_at": {
-            "type": "string"
-          }
-        },
-        "required": [
-          "memory_id",
-          "title",
-          "scope",
-          "summary",
-          "source",
-          "created_at",
-          "updated_at",
-          "revision",
-          "body"
-        ],
-        "type": "object"
-      }
-    },
-    "required": [
-      "action",
-      "memory"
-    ],
-    "type": "object"
-  }
-]New value: +[
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "list"
+      },
+      "memories": {
+        "items": {
+          "additionalProperties": false,
+          "properties": {
+            "memory_id": {
+              "type": "string"
+            },
+            "scope": {
+              "type": "string"
+            },
+            "summary": {
+              "type": "string"
+            },
+            "title": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "memory_id",
+            "title",
+            "scope",
+            "summary"
+          ],
+          "type": "object"
+        },
+        "type": "array"
+      },
+      "project": {
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "projects": {
+        "items": {
+          "type": "string"
+        },
+        "type": "array"
+      }
+    },
+    "required": [
+      "action",
+      "project",
+      "memories",
+      "projects"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "search"
+      },
+      "limit": {
+        "maximum": 5,
+        "minimum": 1,
+        "type": "integer"
+      },
+      "matches": {
+        "items": {
+          "additionalProperties": false,
+          "properties": {
+            "memory_id": {
+              "type": "string"
+            },
+            "passages": {
+              "items": {
+                "additionalProperties": false,
+                "properties": {
+                  "end_char": {
+                    "minimum": 1,
+                    "type": "integer"
+                  },
+                  "start_char": {
+                    "minimum": 0,
+                    "type": "integer"
+                  },
+                  "text": {
+                    "type": "string"
+                  }
+                },
+                "required": [
+                  "text",
+                  "start_char",
+                  "end_char"
+                ],
+                "type": "object"
+              },
+              "minItems": 1,
+              "type": "array"
+            },
+            "rank": {
+              "minimum": 1,
+              "type": "integer"
+            },
+            "revision": {
+              "type": "string"
+            },
+            "scope": {
+              "type": "string"
+            },
+            "summary": {
+              "type": "string"
+            },
+            "title": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "memory_id",
+            "title",
+            "scope",
+            "summary",
+            "revision",
+            "rank",
+            "passages"
+          ],
+          "type": "object"
+        },
+        "type": "array"
+      },
+      "project": {
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "truncated": {
+        "type": "boolean"
+      }
+    },
+    "required": [
+      "action",
+      "project",
+      "limit",
+      "matches",
+      "truncated"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "get"
+      },
+      "memory": {
+        "additionalProperties": false,
+        "properties": {
+          "body": {
+            "type": "string"
+          },
+          "created_at": {
+            "type": "string"
+          },
+          "memory_id": {
+            "type": "string"
+          },
+          "revision": {
+            "type": "string"
+          },
+          "scope": {
+            "type": "string"
+          },
+          "summary": {
+            "type": "string"
+          },
+          "title": {
+            "type": "string"
+          },
+          "updated_at": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "memory_id",
+          "title",
+          "scope",
+          "summary",
+          "created_at",
+          "updated_at",
+          "revision",
+          "body"
+        ],
+        "type": "object"
+      }
+    },
+    "required": [
+      "action",
+      "memory"
+    ],
+    "type": "object"
+  }
+]
    • Changedmemory_write4 fields changed
      • removedInput schema / additionalProperties
        Removed value: -false
      • addedInput schema / oneOf
        Added value: +[
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "create"
+      },
+      "body": {
+        "type": "string"
+      },
+      "project": {
+        "type": "string"
+      },
+      "summary": {
+        "type": "string"
+      },
+      "title": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action",
+      "title",
+      "summary",
+      "body"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "patch"
+      },
+      "base_revision": {
+        "type": "string"
+      },
+      "edits": {
+        "items": {
+          "additionalProperties": false,
+          "properties": {
+            "new_text": {
+              "type": "string"
+            },
+            "old_text": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "old_text",
+            "new_text"
+          ],
+          "type": "object"
+        },
+        "minItems": 1,
+        "type": "array"
+      },
+      "memory_id": {
+        "type": "string"
+      },
+      "summary": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action",
+      "memory_id",
+      "base_revision",
+      "edits"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "action": {
+        "const": "replace"
+      },
+      "base_revision": {
+        "type": "string"
+      },
+      "body": {
+        "type": "string"
+      },
+      "memory_id": {
+        "type": "string"
+      },
+      "summary": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "action",
+      "memory_id",
+      "base_revision",
+      "summary",
+      "body"
+    ],
+    "type": "object"
+  }
+]
      • removedInput schema / properties
        Removed value: -{
-  "action": {
-    "enum": [
-      "create",
-      "patch",
-      "replace"
-    ],
-    "type": "string"
-  },
-  "base_revision": {
-    "type": "string"
-  },
-  "body": {
-    "type": "string"
-  },
-  "edits": {
-    "items": {
-      "additionalProperties": false,
-      "properties": {
-        "new_text": {
-          "type": "string"
-        },
-        "old_text": {
-          "type": "string"
-        }
-      },
-      "required": [
-        "old_text",
-        "new_text"
-      ],
-      "type": "object"
-    },
-    "minItems": 1,
-    "type": "array"
-  },
-  "memory_id": {
-    "type": "string"
-  },
-  "project": {
-    "type": "string"
-  },
-  "summary": {
-    "type": "string"
-  },
-  "title": {
-    "type": "string"
-  }
-}
      • removedInput schema / required
        Removed value: -[
-  "action"
-]
  2. 3 tool updatesv0.1.0
    • First observedmemory_delete
    • First observedmemory_read
    • First observedmemory_write
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.2/5.0
Disambiguation5/5

Each tool handles a distinct lifecycle operation: reading/querying, writing/updating, and deleting memories. There is no overlap between the primary actions, and the sub-modes within memory_read are explicitly separated (list, search, get).

Naming Consistency5/5

All tool names follow the same memory_verb pattern using clear, lowercase snake_case verbs. The naming makes the operation type immediately obvious and perfectly consistent across the set.

Tool Count5/5

Three tools is a compact but complete surface for a permanent memory store. Each tool earns its place, and no redundant or extraneous operations exist.

Completeness5/5

The set covers the full lifecycle: create/modify via memory_write, read via memory_read (including list/search/get), and delete via memory_delete. Revision-handling and Git-history recovery details further round out the functionality, leaving no critical gaps.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive

Resources

Related MCP Connectors

Related MCP Servers

  • phren

    alaarab
    A
    license
    Not graded
    quality
    A
    maintenance
    A persistent memory server for AI agents that stores findings, tasks, and patterns in Markdown files within a git repository, enabling context injection across multiple AI tools.
    4
    MIT

  • Hypermnesic

    leonardsellem
    A
    license
    A
    quality
    A
    maintenance
    Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.
    7
    8
    AGPL 3.0

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/scarletkc/Perenna'

If you have feedback or need assistance with the MCP directory API, please join our Discord server